4.11.2.9 Underwater Imaging, Restoration

Dong, Y.T.[Yan-Ting], Carin, L.[Lawrence],
Rate-distortion analysis of discrete-HMM pose estimation via multiaspect scattering data,
PAMI(25), No. 7, July 2003, pp. 872-883.
IEEE Abstract. 0307
Pose from sequence of scattered waveforms. Apply to underwater. BibRef

Li, Q.Z.[Qing-Zhong], Wang, W.J.[Wen-Jin],
Low-bit-rate coding of underwater color image using improved wavelet difference reduction,
JVCIR(21), No. 7, October 2010, pp. 762-769.
Elsevier DOI 1003
Wavelet difference reduction (WDR), Underwater image compression; Wavelet transform, Low-bit-rate coding, Underwater acoustic channel; Underwater color image, Underwater observation, Wavelet tree, Image transmission BibRef

Telem, G.[Gili], Filin, S.[Sagi],
Photogrammetric modeling of underwater environments,
PandRS(65), No. 5, September 2010, pp. 433-444.
Elsevier DOI 1003
Underwater photogrammetry, Close-range, Calibration, Estimation BibRef

Telem, G.[Gili], Filin, S.[Sagi],
Photogrammetric modeling of the relative orientation in underwater environments,
PandRS(86), No. 1, 2013, pp. 150-156.
Elsevier DOI 1312
Underwater photogrammetry BibRef

Chiang, J.Y.[John Y.], Chen, Y.C.[Ying-Ching],
Underwater Image Enhancement by Wavelength Compensation and Dehazing,
IP(21), No. 4, April 2012, pp. 1756-1769.
IEEE DOI 1204
BibRef

Chiang, J.Y.[John Y.], Chen, Y.C.[Ying-Ching], Chen, Y.F.[Yung-Fu],
Underwater Image Enhancement: Using Wavelength Compensation and Image Dehazing (WCID),
ACIVS11(372-383).
Springer DOI 1108
BibRef

Garaba, S.P.[Shungudzemwoyo P.], Voß, D.[Daniela], Zielinski, O.[Oliver],
Physical, Bio-Optical State and Correlations in North-Western European Shelf Seas,
RS(6), No. 6, 2014, pp. 5042-5066.
DOI Link 1407
Understanding underwater properties by color. BibRef

Li, C.Y., Guo, J.C., Cong, R.M., Pang, Y.W., Wang, B.,
Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior,
IP(25), No. 12, December 2016, pp. 5664-5677.
IEEE DOI 1612
geophysical image processing BibRef

Liu, X.P.[Xiao-Peng], Zhong, G.Q.[Guo-Qiang], Liu, C.[Cong], Dong, J.Y.[Jun-Yu],
Underwater image colour constancy based on DSNMF,
IET-IPR(11), No. 1, January 2017, pp. 38-43.
DOI Link 1703
BibRef

Churnside, J.H.[James H.], Marchbanks, R.D.[Richard D.], Lembke, C.[Chad], Beckler, J.[Jordon],
Optical Backscattering Measured by Airborne Lidar and Underwater Glider,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Park, D.[Dubok], Han, D.K.[David K.], Ko, H.S.[Han-Seok],
Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising,
IEICE(E100-D), No. 7, July 2017, pp. 1475-1483.
WWW Link. 1708
BibRef

Li, C.Y.[Chong-Yi], Guo, J.C.[Ji-Chang], Guo, C.L.[Chun-Le], Cong, R.M.[Run-Min], Gong, J.C.[Jia-Chang],
A hybrid method for underwater image correction,
PRL(94), No. 1, 2017, pp. 62-67.
Elsevier DOI 1708
Underwater, image, correction BibRef

Ancuti, C.O.[Codruta O.], Ancuti, C.[Cosmin], de Vleeschouwer, C.[Christophe], Bekaert, P.[Philippe],
Color Balance and Fusion for Underwater Image Enhancement,
IP(27), No. 1, January 2018, pp. 379-393.
IEEE DOI 1712
cameras, image colour analysis, image denoising, image enhancement, image fusion, image restoration, image segmentation, white-balancing
See also Single Image Dehazing by Multi-Scale Fusion.
See also Single-Scale Fusion: An Effective Approach to Merging Images. BibRef

Ancuti, C.[Cosmin], Ancuti, C.O.[Codruta Orniana], Haber, T.[Tom], Bekaert, P.[Philippe],
Enhancing underwater images and videos by fusion,
CVPR12(81-88).
IEEE DOI 1208
BibRef
Earlier: A2, A1, A3, A4:
Fusion-based restoration of the underwater images,
ICIP11(1557-1560).
IEEE DOI 1201
BibRef

Ancuti, C.O.[Codruta O.], Ancuti, C.[Cosmin], de Vleeschouwer, C., Garcia, R., Bovik, A.C.,
Multi-scale underwater descattering,
ICPR16(4202-4207)
IEEE DOI 1705
Estimation, Image color analysis, Image restoration, Lighting, Mathematical model, Optical imaging, Optical, scattering BibRef

Ancuti, C.O.[Codruta O.], Ancuti, C.[Cosmin], de Vleeschouwer, C., Garcia, R.,
Locally Adaptive Color Correction for Underwater Image Dehazing and Matching,
NTIRE17(997-1005)
IEEE DOI 1709
Attenuation, Channel estimation, Image color analysis, Image restoration, Light sources, Lighting BibRef

Emberton, S.[Simon], Chittka, L.[Lars], Cavallaro, A.[Andrea],
Underwater image and video dehazing with pure haze region segmentation,
CVIU(168), 2018, pp. 145-156.
Elsevier DOI 1804
Dehazing, Image processing, Segmentation, Underwater, White balancing, Video processing BibRef

Hou, G.J.[Guo-Jia], Pan, Z.K.[Zhen-Kuan], Huang, B.X.[Bao-Xiang], Wang, G.D.[Guo-Dong], Luan, X.[Xin],
Hue preserving-based approach for underwater colour image enhancement,
IET-IPR(12), No. 2, February 2018, pp. 292-298.
DOI Link 1801
BibRef

Jian, M.[Muwei], Qi, Q.A.[Qi-Ang], Dong, J.Y.[Jun-Yu], Yin, Y.L.[Yi-Long], Lam, K.M.[Kin-Man],
Integrating QDWD with pattern distinctness and local contrast for underwater saliency detection,
JVCIR(53), 2018, pp. 31-41.
Elsevier DOI 1805
Underwater image, Saliency detection, QDWD, Pattern distinctness, Local contrast BibRef

Barros, W.[Wagner], Nascimento, E.R.[Erickson R.], Barbosa, W.V.[Walysson V.], Campos, M.F.M.[Mario F.M.],
Single-shot underwater image restoration: A visual quality-aware method based on light propagation model,
JVCIR(55), 2018, pp. 363-373.
Elsevier DOI 1809
Image restoration, Underwater vision, Feature-preserving, Visibility, Inverse problem BibRef

Mangeruga, M.[Marino], Bruno, F.[Fabio], Cozza, M.[Marco], Agrafiotis, P.[Panagiotis], Skarlatos, D.[Dimitrios],
Guidelines for Underwater Image Enhancement Based on Benchmarking of Different Methods,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Mangeruga, M.[Marino], Casavola, A.[Alessandro], Pupo, F.[Francesco], Bruno, F.[Fabio],
An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zhou, Y., Wu, Q., Yan, K., Feng, L., Xiang, W.,
Underwater Image Restoration Using Color-Line Model,
CirSysVideo(29), No. 3, March 2019, pp. 907-911.
IEEE DOI 1903
Image color analysis, Degradation, Image restoration, Estimation, Atmospheric modeling, Mathematical model, Atmospheric waves, ocean optics BibRef

Sun, X.[Xin], Liu, L.P.[Li-Peng], Li, Q.[Qiong], Dong, J.Y.[Jun-Yu], Lima, E.[Estanislau], Yin, R.Y.[Rui-Ying],
Deep pixel-to-pixel network for underwater image enhancement and restoration,
IET-IPR(13), No. 3, February 2019, pp. 469-474.
DOI Link 1903
BibRef

Tang, C.[Chong], von Lukas, U.F.[Uwe Freiherr], Vahl, M.[Matthias], Wang, S.[Shuo], Wang, Y.[Yu], Tan, M.[Min],
Efficient underwater image and video enhancement based on Retinex,
SIViP(13), No. 5, July 2019, pp. 1011-1018.
Springer DOI 1906
BibRef

Sánchez-Ferreira, C., Coelho, L.S., Ayala, H.V.H., Farias, M.C.Q., Llanos, C.H.,
Bio-inspired optimization algorithms for real underwater image restoration,
SP:IC(77), 2019, pp. 49-65.
Elsevier DOI 1906
Underwater image processing, Bio-inspired optimization, Image quality assessment, Image formation models BibRef

Elnashef, B.[Bashar], Filin, S.[Sagi],
Direct linear and refraction-invariant pose estimation and calibration model for underwater imaging,
PandRS(154), 2019, pp. 259-271.
Elsevier DOI 1907
Flat refractive, Underwater, Imaging, Pose estimation, Calibration BibRef

Wang, K.Y.[Ke-Yan], Hu, Y.[Yan], Chen, J.[Jun], Wu, X.Y.[Xian-Yun], Zhao, X.[Xi], Li, Y.S.[Yun-Song],
Underwater Image Restoration Based on a Parallel Convolutional Neural Network,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Raihan, A.J.[A. Jarina], Abas, P.E.[Pg Emeroylariffion], de Silva, L.C.[Liyanage C.],
Review of underwater image restoration algorithms,
IET-IPR(13), No. 10, 22 August 2019, pp. 1587-1596.
DOI Link 1909
BibRef

Li, C.Y.[Chong-Yi], Anwar, S.[Saeed], Porikli, F.M.[Fatih M.],
Underwater scene prior inspired deep underwater image and video enhancement,
PR(98), 2020, pp. 107038.
Elsevier DOI 1911
Underwater image and video enhancement and restoration, Underwater image synthesis, Deep learning BibRef

Anwar, S.[Saeed], Li, C.Y.[Chong-Yi],
Diving deeper into underwater image enhancement: A survey,
SP:IC(89), 2020, pp. 115978.
Elsevier DOI 2010
Survey, Underwater Images. Underwater image enhancement, Deep learning, Convolutional neural networks (CNNs), Survey BibRef

Zhuang, P.X.[Pei-Xian], Wu, J.[Jiamin], Porikli, F.M.[Fatih M.], Li, C.Y.[Chong-Yi],
Underwater Image Enhancement With Hyper-Laplacian Reflectance Priors,
IP(31), 2022, pp. 5442-5455.
IEEE DOI 2208
Image color analysis, Lighting, Image enhancement, Laplace equations, Scattering, Optimization, Estimation, alternative optimization BibRef

Zhuang, P.X.[Pei-Xian],
Retinex Underwater Image Enhancement With Multiorder Gradient Priors,
ICIP21(1709-1713)
IEEE DOI 2201
Reflectivity, Image color analysis, Piecewise linear approximation, Noise reduction, Lighting, Imaging, alternative optimization BibRef

Purohit, K.[Kuldeep], Mandal, S.[Srimanta], Rajagopalan, A.N.,
Multilevel weighted enhancement for underwater image dehazing,
JOSA-A(36), No. 6, June 2019, pp. 1098-1108.
DOI Link 1912
Attenuation coefficient, Forward scattering, Image processing, Image quality, Light transmission, Underwater imaging BibRef

Yang, M.[Miao], Hu, K.[Ke], Du, Y.X.[Yi-Xiang], Wei, Z.Q.[Zhi-Qiang], Sheng, Z.B.[Zhi-Bin], Hu, J.T.[Jin-Tong],
Underwater Image Enhancement Based on Conditional Generative Adversarial Network,
SP:IC(81), 2020, pp. 115723.
Elsevier DOI 1912
Underwater image enhancement, Conditional generative adversarial networks, Deep learning BibRef

Li, C.Y.[Chong-Yi], Guo, C.L.[Chun-Le], Ren, W.Q.[Wen-Qi], Cong, R.M.[Run-Min], Hou, J.H.[Jun-Hui], Kwong, S.[Sam], Tao, D.C.[Da-Cheng],
An Underwater Image Enhancement Benchmark Dataset and Beyond,
IP(29), 2020, pp. 4376-4389.
IEEE DOI 2002
Image enhancement, Image color analysis, Benchmark testing, Image restoration, Training, deep learning BibRef

Jiang, Q.P.[Qiu-Ping], Gu, Y.[Yuese], Li, C.Y.[Chong-Yi], Cong, R.M.[Run-Min], Shao, F.[Feng],
Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric,
CirSysVideo(32), No. 9, September 2022, pp. 5959-5974.
IEEE DOI 2209
Measurement, Image quality, Benchmark testing, Image color analysis, Visualization, Image enhancement, pairwise comparison
See also Benchmark Dataset and Pair-Wise Ranking Method for Quality Evaluation of Night-Time Image Enhancement. BibRef

Hou, G.J.[Guo-Jia], Li, J.M.[Jing-Ming], Wang, G.D.[Guo-Dong], Yang, H.[Huan], Huang, B.X.[Bao-Xiang], Pan, Z.K.[Zhen-Kuan],
A novel dark channel prior guided variational framework for underwater image restoration,
JVCIR(66), 2020, pp. 102732.
Elsevier DOI 2003
Underwater image restoration, Dehazing and denoising, UTV, ADMM, UDCP BibRef

Chadebecq, F.[François], Vasconcelos, F.[Francisco], Lacher, R.[René], Maneas, E.[Efthymios], Desjardins, A.[Adrien], Ourselin, S.[Sébastien], Vercauteren, T.[Tom], Stoyanov, D.[Danail],
Refractive Two-View Reconstruction for Underwater 3D Vision,
IJCV(128), No. 5, May 2020, pp. 1101-1117.
Springer DOI 2005
BibRef

Dudhane, A., Hambarde, P., Patil, P., Murala, S.,
Deep Underwater Image Restoration and Beyond,
SPLetters(27), 2020, pp. 675-679.
IEEE DOI 2005
Image restoration, Image color analysis, Image enhancement, Distortion, Feature extraction, Image databases, Task analysis, underwater haze BibRef

Fu, X.Y.[Xue-Yang], Cao, X.Y.[Xiang-Yong],
Underwater image enhancement with global-local networks and compressed-histogram equalization,
SP:IC(86), 2020, pp. 115892.
Elsevier DOI 2006
Underwater image, Deep learning, Image enhancement, CNNs BibRef

Jiang, Q.[Qin], Chen, Y.[Yang], Wang, G.Y.[Guo-Yu], Ji, T.T.[Ting-Ting],
A novel deep neural network for noise removal from underwater image,
SP:IC(87), 2020, pp. 115921.
Elsevier DOI 2007
Underwater image, Noise removal, Generative adversarial network, Self-attention, Spectral normalization BibRef

Helmholz, P.[Petra], Lichti, D.D.[Derek D.],
Investigation of Chromatic Aberration and Its Influence on the Processing of Underwater Imagery,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Jian, M.[Muwei], Liu, X.Y.[Xiang-Yu], Luo, H.J.[Han-Jiang], Lu, X.W.[Xiang-Wei], Yu, H.[Hui], Dong, J.Y.[Jun-Yu],
Underwater image processing and analysis: A review,
SP:IC(91), 2021, pp. 116088.
Elsevier DOI 2012
Underwater image, Marine environment, Underwater saliency detection, Color? constancy BibRef

Yuan, F.[Fei], Zhan, L.H.[Li-Hui], Pan, P.[Panwang], Cheng, E.[En],
Low bit-rate compression of underwater image based on human visual system,
SP:IC(91), 2021, pp. 116082.
Elsevier DOI 2012
Underwater image compression, Chroma masking, Visual masking, Hybrid wavelets and directional filter banks(DFBs) BibRef

Reggiannini, M.[Marco], Moroni, D.[Davide],
The Use of Saliency in Underwater Computer Vision: A Review,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Lin, Y., Shen, L., Wang, Z., Wang, K., Zhang, X.,
Attenuation Coefficient Guided Two-Stage Network for Underwater Image Restoration,
SPLetters(28), 2021, pp. 199-203.
IEEE DOI 2102
Distortion, Attenuation, Image restoration, Estimation, Absorption, Scattering, Optical distortion, underwater physical model BibRef

Li, Y.[Yang], Chen, R.[Rong],
SE-RWNN: an synergistic evolution and randomly wired neural network-based model for adaptive underwater image enhancement,
IET-IPR(14), No. 16, 19 December 2020, pp. 4349-4358.
DOI Link 2103
BibRef

Yang, N.[Ning], Zhong, Q.H.[Qi-Hang], Li, K.[Kun], Cong, R.M.[Run-Min], Zhao, Y.[Yao], Kwong, S.[Sam],
A reference-free underwater image quality assessment metric in frequency domain,
SP:IC(94), 2021, pp. 116218.
Elsevier DOI 2104
Underwater image, Reference-free image quality assessment, Frequency domain, Dark channel prior weighting, New dataset BibRef

Xue, X.W.[Xin-Wei], Hao, Z.H.[Zhen-Hua], Ma, L.[Long], Wang, Y.[Yi], Liu, R.S.[Ri-Sheng],
Joint Luminance and Chrominance Learning for Underwater Image Enhancement,
SPLetters(28), 2021, pp. 818-822.
IEEE DOI 2105
BibRef

Hou, M.J.[Min-Jun], Liu, R.S.[Ri-Sheng], Fan, X.[Xin], Luo, Z.X.[Zhong-Xuan],
Joint Residual Learning for Underwater Image Enhancement,
ICIP18(4043-4047)
IEEE DOI 1809
Image color analysis, Training, Image quality, Attenuation, Convolution, Image enhancement, Task analysis, illumination balance BibRef

Li, C.Y.[Chong-Yi], Anwar, S.[Saeed], Hou, J.H.[Jun-Hui], Cong, R.M.[Run-Min], Guo, C.[Chunle], Ren, W.Q.[Wen-Qi],
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding,
IP(30), 2021, pp. 4985-5000.
IEEE DOI 2106
Image color analysis, Image enhancement, Imaging, Visualization, Decoding, Feature extraction, Scattering, Underwater imaging, scattering removal BibRef

Yang, X.[Xi], Li, H.[Hui], Chen, R.[Rong],
Underwater image enhancement with image colorfulness measure,
SP:IC(95), 2021, pp. 116225.
Elsevier DOI 2106
Deep learning, Underwater enhancement BibRef

Wang, H.[Huan], Wu, H.[Hao], Hu, Q.[Qian], Chi, J.N.[Jian-Ning], Yu, X.S.[Xiao-Sheng], Wu, C.D.[Cheng-Dong],
Underwater image super-resolution using multi-stage information distillation networks,
JVCIR(77), 2021, pp. 103136.
Elsevier DOI 2106
Underwater image, Super-resolution, Visually-guided underwater robots, Convolutional neural network BibRef

Li, H.Y.[Han-Yu], Zhuang, P.X.[Pei-Xian],
DewaterNet: A fusion adversarial real underwater image enhancement network,
SP:IC(95), 2021, pp. 116248.
Elsevier DOI 2106
Real underwater image enhancement, Generative adversarial network, Benchmark dataset, Deep learning BibRef

Wang, Y.D.[Yu-Dong], Guo, J.C.[Ji-Chang], Gao, H.[Huan], Yue, H.[Huihui],
UIEC^2-Net: CNN-based underwater image enhancement using two color space,
SP:IC(96), 2021, pp. 116250.
Elsevier DOI 2106
Underwater image enhancement, HSV color space, Deep learning BibRef

Fayaz, S.[Sheezan], Parah, S.A.[Shabir A.], Qureshi, G.J., Kumar, V.[Vijaya],
Underwater image restoration: A state-of-the-art review,
IET-IPR(15), No. 2, 2021, pp. 269-285.
DOI Link 2106
BibRef

Li, Y.[Yang], Chen, R.[Rong],
UDA-Net: Densely attention network for underwater image enhancement,
IET-IPR(15), No. 3, 2021, pp. 774-785.
DOI Link 2106
BibRef

Zhang, H.Q.[Hui-Qing], Sun, L.[Luyu], Wu, L.F.[Li-Fang], Gu, K.[Ke],
DuGAN: An effective framework for underwater image enhancement,
IET-IPR(15), No. 9, 2021, pp. 2010-2019.
DOI Link 2106
BibRef

Berman, D.[Dana], Levy, D.[Deborah], Avidan, S.[Shai], Treibitz, T.[Tali],
Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset,
PAMI(43), No. 8, August 2021, pp. 2822-2837.
IEEE DOI 2107
Image color analysis, Attenuation, Image restoration, Channel estimation, Cameras, image color analysis
See also Single Image Dehazing Using Haze-Lines. BibRef

Levy, D.[Deborah], Levy, D.[Deborah], Belfer, Y.[Yuval], Osherov, E.[Elad], Bigal, E.[Eyal], Scheinin, A.P.[Aviad P.], Nativ, H.[Hagai], Tchernov, D.[Dan], Treibitz, T.[Tali],
Automated Analysis of Marine Video with Limited Data,
Environmental18(1466-14668)
IEEE DOI 1812
Detectors, Training, Organisms, Object detection, Task analysis, Feature extraction, Lighting BibRef

Akkaynak, D., Treibitz, T.,
A Revised Underwater Image Formation Model,
CVPR18(6723-6732)
IEEE DOI 1812
Attenuation, Scattering, Atmospheric modeling, Image color analysis, Mathematical model, Oceans, Absorption BibRef

Zhu, D.[Daqi], Liu, Z.Q.[Zhi-Qiang], Zhang, Y.[Youmin],
Underwater image enhancement based on colour correction and fusion,
IET-IPR(15), No. 11, 2021, pp. 2591-2603.
DOI Link 2108
BibRef

Montes-Herrera, J.C.[Juan C.], Cimoli, E.[Emiliano], Cummings, V.[Vonda], Hill, N.[Nicole], Lucieer, A.[Arko], Lucieer, V.[Vanessa],
Underwater Hyperspectral Imaging (UHI): A Review of Systems and Applications for Proximal Seafloor Ecosystem Studies,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Ding, X.Y.[Xue-Yan], Liang, Z.[Zheng], Wang, Y.[Yafei], Fu, X.P.[Xian-Ping],
Depth-aware total variation regularization for underwater image dehazing,
SP:IC(98), 2021, pp. 116408.
Elsevier DOI 2109
Underwater image dehazing, Optimization function, Normalized scene depth BibRef

Yuan, J.Y.[Jie-Yu], Cao, W.[Wei], Cai, Z.C.[Zhan-Chuan], Su, B.H.[Bing-Hua],
An Underwater Image Vision Enhancement Algorithm Based on Contour Bougie Morphology,
GeoRS(59), No. 10, October 2021, pp. 8117-8128.
IEEE DOI 2109
Image color analysis, Scattering, Image enhancement, Morphology, Degradation, Image quality, Optical imaging, Contrast enhancement, underwater image BibRef

Yang, M.[Miao], Yin, G.[Ge], Du, Y.X.[Yi-Xiang], Wei, Z.Q.[Zhi-Qiang],
Pair comparison based progressive subjective quality ranking for underwater images,
SP:IC(99), 2021, pp. 116444.
Elsevier DOI 2111
Subjective image quality evaluation, Mean opinion score, Quality ranking, Underwater image, Image quality database BibRef

Jiang, Q.[Qun], Zhang, Y.F.[Yun-Feng], Bao, F.X.[Fang-Xun], Zhao, X.Y.[Xiu-Yang], Zhang, C.M.[Cai-Ming], Liu, P.[Peide],
Two-step domain adaptation for underwater image enhancement,
PR(122), 2022, pp. 108324.
Elsevier DOI 2112
Underwater image enhancement, Transfer learning, Domain adaptation, Cycle-consistent adversarial network BibRef

Hu, J.K.[Jun-Kang], Jiang, Q.P.[Qiu-Ping], Cong, R.M.[Run-Min], Gao, W.[Wei], Shao, F.[Feng],
Two-Branch Deep Neural Network for Underwater Image Enhancement in HSV Color Space,
SPLetters(28), 2021, pp. 2152-2156.
IEEE DOI 2112
Image color analysis, Degradation, Deep learning, Image enhancement, Training, Generators, convolutional neural network BibRef

Li, X.B.[Xin-Bin], Lei, C.B.[Cheng-Bo], Yu, H.F.[Hai-Feng], Feng, Y.K.[Yan-Kai],
Underwater image restoration by color compensation and color-line model,
SP:IC(101), 2022, pp. 116569.
Elsevier DOI 2201
Underwater image restoration, Color-line model, Color compensation, Attenuation coefficient BibRef

Fu, Z.Q.[Zhen-Qi], Fu, X.Y.[Xue-Yang], Huang, Y.[Yue], Ding, X.H.[Xing-Hao],
Twice Mixing: A rank learning based quality assessment approach for underwater image enhancement,
SP:IC(102), 2022, pp. 116622.
Elsevier DOI 2202
Underwater image, Quality assessment, Mixing, Rank learning, Siamese Network BibRef

Mathur, M.[Monika], Goel, N.[Nidhi],
Enhancement algorithm for high visibility of underwater images,
IET-IPR(16), No. 4, 2022, pp. 1067-1082.
DOI Link 2203
BibRef

Qi, Q.[Qi], Zhang, Y.C.[Yong-Chang], Tian, F.[Fei], Wu, Q.M.J.[Q. M. Jonathan], Li, K.Q.[Kun-Qian], Luan, X.[Xin], Song, D.L.[Da-Lei],
Underwater Image Co-Enhancement With Correlation Feature Matching and Joint Learning,
CirSysVideo(32), No. 3, March 2022, pp. 1133-1147.
IEEE DOI 2203
Image enhancement, Correlation, Task analysis, Degradation, Deep learning, Visualization, Underwater image enhancement, correlation feature matching BibRef

Yang, H.[Hua], Tian, F.[Fei], Qi, Q.[Qi], Wu, Q.M.J.[Q. M. Jonathan], Li, K.[Kunqian],
Underwater image enhancement with latent consistency learning-based color transfer,
IET-IPR(16), No. 6, 2022, pp. 1594-1612.
DOI Link 2204
BibRef

Li, K.Q.[Kun-Qian], Fan, H.T.[Hong-Tao], Qi, Q.[Qi], Yan, C.[Chi], Sun, K.[Kun], Wu, Q.M.J.[Q. M. Jonathan],
TCTL-Net: Template-Free Color Transfer Learning for Self-Attention Driven Underwater Image Enhancement,
CirSysVideo(34), No. 6, June 2024, pp. 4682-4697.
IEEE DOI Code:
HTML Version. 2406
Image color analysis, Image enhancement, Visualization, Training, Image resolution, Degradation, Task analysis, differentiated enhancement BibRef

Yan, X.H.[Xiao-Hong], Wang, G.X.[Guang-Xin], Wang, G.Y.[Guang-Yuan], Wang, Y.F.[Ya-Fei], Fu, X.P.[Xian-Ping],
A novel biologically-inspired method for underwater image enhancement,
SP:IC(104), 2022, pp. 116670.
Elsevier DOI 2204
Underwater image, Biological vision, Color constancy, Luminance adaptation BibRef

Gangisetty, S.[Shankar], Rai, R.R.[Raghu Raj],
FloodNet: Underwater image restoration based on residual dense learning,
SP:IC(104), 2022, pp. 116647.
Elsevier DOI 2204
Underwater image restoration, Residual dense block, Global feature fusion, Convolutional neural network, UIEB dataset BibRef

Vasilkov, A.[Alexander], Krotkov, N.[Nickolay], Haffner, D.[David], Fasnacht, Z.[Zachary], Joiner, J.[Joanna],
Estimates of Hyperspectral Surface and Underwater UV Planar and Scalar Irradiances from OMI Measurements and Radiative Transfer Computations,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Vasilkov, A.[Alexander], Krotkov, N.[Nickolay], Bandel, M.[Matthew], Jethva, H.[Hiren], Haffner, D.[David], Fasnacht, Z.[Zachary], Torres, O.[Omar], Ahn, C.W.[Chang-Woo], Joiner, J.[Joanna],
Absorbing Aerosol Effects on Hyperspectral Surface and Underwater UV Irradiances from OMI Measurements and Radiative Transfer Computations,
RS(17), No. 3, 2025, pp. 562.
DOI Link 2502
BibRef

Xie, J.[Jun], Hou, G.J.[Guo-Jia], Wang, G.D.[Guo-Dong], Pan, Z.K.[Zhen-Kuan],
A Variational Framework for Underwater Image Dehazing and Deblurring,
CirSysVideo(32), No. 6, June 2022, pp. 3514-3526.
IEEE DOI 2206
Scattering, Image restoration, Image color analysis, Channel estimation, Kernel, Cameras, Estimation, Complete UIFM, ADMM BibRef

Wang, L.[Li], Xu, L.Z.[Li-Zhong], Tian, W.[Wei], Zhang, Y.F.[Yun-Fei], Feng, H.[Hui], Chen, Z.[Zhe],
Underwater image super-resolution and enhancement via progressive frequency-interleaved network,
JVCIR(86), 2022, pp. 103545.
Elsevier DOI 2206
Underwater image, Super-resolution, Enhancement, Deep learning, Frequency domain BibRef

He, Y.T.[Yun-Tao], Liu, Y.J.[Yong-Jun], Liu, C.[Chang], Li, D.[Duan],
Analysis of Transmission Depth and Photon Number in Monte Carlo Simulation for Underwater Laser Transmission,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Gu, C.J.[Chang-Jun], Cong, Y.[Yang], Sun, G.[Gan], Gao, Y.J.[Ya-Jun], Tang, X.[Xu], Zhang, T.[Tao], Fan, B.J.[Bao-Jie],
MedUCC: Medium-Driven Underwater Camera Calibration for Refractive 3-D Reconstruction,
SMCS(52), No. 9, September 2022, pp. 5937-5948.
IEEE DOI 2208
Cameras, Calibration, Glass, Solid modeling, Computational modeling, Robot vision systems, Pose estimation, underwater vision BibRef

Zheng, Y.N.[Yan-Nan], Chen, W.L.[Wei-Ling], Lin, R.F.[Rong-Fu], Zhao, T.S.[Tie-Song], Le Callet, P.[Patrick],
UIF: An Objective Quality Assessment for Underwater Image Enhancement,
IP(31), 2022, pp. 5456-5468.
IEEE DOI 2208
Measurement, Indexes, Databases, Image quality, Visualization, Imaging, Task analysis, Image quality assessment (IQA), underwater image processing BibRef

Sun, K.C.[Kai-Chuan], Meng, F.[Fei], Tian, Y.[Yubo],
Progressive multi-branch embedding fusion network for underwater image enhancement,
JVCIR(87), 2022, pp. 103587.
Elsevier DOI 2208
Underwater image enhancement, Marine snow removal, Multi-branch embedding fusion, Multi-stage framework BibRef

Song, H.J.[Hua-Jun], Chang, L.[Laibin], Chen, Z.W.[Zi-Wei], Ren, P.[Peng],
Enhancement-Registration-Homogenization (ERH): A Comprehensive Underwater Visual Reconstruction Paradigm,
PAMI(44), No. 10, October 2022, pp. 6953-6967.
IEEE DOI 2209
Image color analysis, Image reconstruction, Visualization, Nonhomogeneous media, Image restoration, Image fusion, underwater image reconstruction BibRef

Lin, P.[Peng], Wang, Y.[Yafei], Wang, G.Y.[Guang-Yuan], Yan, X.H.[Xiao-Hong], Jiang, G.Q.[Guang-Qi], Fu, X.P.[Xian-Ping],
Conditional generative adversarial network with dual-branch progressive generator for underwater image enhancement,
SP:IC(108), 2022, pp. 116805.
Elsevier DOI 2209
Underwater image enhancement, Progressive enhancement, Dual-branch generator, Deep learning BibRef

Han, J.L.[Jun-Lin], Shoeiby, M.[Mehrdad], Malthus, T.[Tim], Botha, E.[Elizabeth], Anstee, J.[Janet], Anwar, S.[Saeed], Wei, R.[Ran], Armin, M.A.[Mohammad Ali], Li, H.D.[Hong-Dong], Petersson, L.[Lars],
Underwater Image Restoration via Contrastive Learning and a Real-World Dataset,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Jiang, N.F.[Nan-Feng], Chen, W.L.[Wei-Ling], Lin, Y.T.[Yu-Ting], Zhao, T.S.[Tie-Song], Lin, C.W.[Chia-Wen],
Underwater Image Enhancement With Lightweight Cascaded Network,
MultMed(24), 2022, pp. 4301-4313.
IEEE DOI 2210
Image color analysis, Task analysis, Visualization, Physics, Mathematical models, Complexity theory, Laplace equations, oceanic image processing BibRef

Shi, Z.H.[Zheng-Hao], Wang, Y.L.[Yong-Li], Zhou, Z.[Zhaorun], Ren, W.Q.[Wen-Qi],
Integrating deep learning and traditional image enhancement techniques for underwater image enhancement,
IET-IPR(16), No. 13, 2022, pp. 3471-3484.
DOI Link 2210
BibRef

Xue, X.W.[Xin-Wei], Li, Z.X.[Ze-Xuanxo], Ma, L.[Long], Jia, Q.[Qi], Liu, R.S.[Ri-Sheng], Fan, X.[Xin],
Investigating intrinsic degradation factors by multi-branch aggregation for real-world underwater image enhancement,
PR(133), 2023, pp. 109041.
Elsevier DOI 2210
Underwater image enhancement, Multi-branch learning, Real-world underwater images, Comprehensive evaluation BibRef

Wu, J.J.[Jun-Jun], Liu, X.L.[Xi-Lin], Lu, Q.H.[Qing-Hua], Lin, Z.[Zeqin], Qin, N.[Ningwei], Shi, Q.W.[Qing-Wu],
FW-GAN: Underwater image enhancement using generative adversarial network with multi-scale fusion,
SP:IC(109), 2022, pp. 116855.
Elsevier DOI 2210
Underwater robot, Image enhancement, Generative adversarial network, Generalization capability, Deep learning BibRef

Qi, Q.[Qi], Li, K.[Kunqian], Zheng, H.Y.[Hai-Yong], Gao, X.[Xiang], Hou, G.J.[Guo-Jia], Sun, K.[Kun],
SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement With Multi-Scale Perception,
IP(31), 2022, pp. 6816-6830.
IEEE DOI 2211
Semantics, Image enhancement, Task analysis, Feature extraction, Training, Degradation, Visualization, Underwater image enhancement, SUIM-E dataset BibRef

Chen, J.[Jian], Wu, H.T.[Hao-Tian], Lu, L.[Lu], Luo, X.Y.[Xiang-Yang], Hu, J.K.[Jian-Kun],
Single underwater image haze removal with a learning-based approach to blurriness estimation,
JVCIR(89), 2022, pp. 103656.
Elsevier DOI 2212
Underwater image, Image dehazing, Image restoration, Image enhancement BibRef

Elnashef, B.[Bashar], Filin, S.[Sagi],
Geometry, calibration, and robust centering procedures for refractive dome-port based imaging systems,
PandRS(194), 2022, pp. 132-151.
Elsevier DOI 2212
Underwater imaging, Dome ports, Calibration, Pose estimation, Centering BibRef

Zhang, C.[Chendi], Sun, A.[Ao'ran], Hassan, M.A.[Marwan A.], Qin, C.[Chao],
Assessing Through-Water Structure-from-Motion Photogrammetry in Gravel-Bed Rivers under Controlled Conditions,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zhang, Y.B.[Yan-Bao], Liu, Y.[Yike], Yi, J.[Jia],
Least-Squares Reverse-Time Migration of Water-Bottom-Related Multiples,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, F.[Fei], Zheng, J.B.[Jiang-Bin], Zhang, Y.F.[Yuan-Fang], Jia, W.J.[Wen-Jing], Wei, Q.[Qianru], He, X.J.[Xiang-Jian],
Cross-domain learning for underwater image enhancement,
SP:IC(110), 2023, pp. 116890.
Elsevier DOI 2212
Unsupervised learning, Underwater image enhancement, GAN, Loss function BibRef

Mei, X.[Xinkui], Ye, X.[Xiufen], Zhang, X.F.[Xiao-Feng], Liu, Y.[Yusong], Wang, J.T.[Jun-Ting], Hou, J.[Jun], Wang, X.L.[Xu-Li],
UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Wang, H.[Hao], Sun, S.X.[Shi-Xin], Ren, P.[Peng],
Meta underwater camera: A smart protocol for underwater image enhancement,
PandRS(195), 2023, pp. 462-481.
Elsevier DOI 2301
Meta underwater camera, Underwater image enhancement, Smart protocol, Reinforcement learning BibRef

Liu, B.[Bohan], Men, S.J.[Shao-Jie], Ding, Z.J.[Zhong-Jun], Li, D.[Dewei], Zhao, Z.G.[Zhi-Gang], He, J.H.[Jia-Hao], Ju, H.C.[Hao-Chen], Shen, M.L.[Meng-Ling], Yu, Q.[Qiuyuan], Liu, Z.J.[Zhao-Jun],
Underwater Hyperspectral Imaging System with Liquid Lenses,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Chang, L.[Laibin], Song, H.J.[Hua-Jun], Li, M.J.[Ming-Jie], Xiang, M.[Ming],
UIDEF: A real-world underwater image dataset and a color-contrast complementary image enhancement framework,
PandRS(196), 2023, pp. 415-428.
Elsevier DOI 2302
Underwater image enhancement, Real-world underwater dataset, Adaptive color balance, Multi-scale weighted fusion, Visual reconstruction BibRef

Wang, Z.Y.[Zheng-Yong], Shen, L.Q.[Li-Quan], Xu, M.[Mai], Yu, M.[Mei], Wang, K.[Kun], Lin, Y.F.[Yu-Fei],
Domain Adaptation for Underwater Image Enhancement,
IP(32), 2023, pp. 1442-1457.
IEEE DOI 2303
Image enhancement, Image color analysis, Adaptation models, Synthetic data, Data models, Training, Degradation, rank-based underwater image quality assessment BibRef

Hao, J.Y.[Jun-Yu], Yang, H.B.[Hong-Bo], Hou, X.[Xia], Zhang, Y.[Yang],
Two-Stage Underwater Image Restoration Algorithm Based on Physical Model and Causal Intervention,
SPLetters(30), 2023, pp. 120-124.
IEEE DOI 2303
Degradation, Image restoration, Attenuation, Generative adversarial networks, Generators, Correlation, Training, causal intervention BibRef

Kang, Y.Z.[Yao-Zu], Jiang, Q.P.[Qiu-Ping], Li, C.Y.[Chong-Yi], Ren, W.Q.[Wen-Qi], Liu, H.T.[Han-Tao], Wang, P.J.[Peng-Jun],
A Perception-Aware Decomposition and Fusion Framework for Underwater Image Enhancement,
CirSysVideo(33), No. 3, March 2023, pp. 988-1002.
IEEE DOI 2303
Visualization, Image color analysis, Image reconstruction, Image enhancement, Fuses, Task analysis, Image quality, image fusion BibRef

Zhang, W.D.[Wei-Dong], Zhou, L.[Ling], Zhuang, P.X.[Pei-Xian], Li, G.[Guohou], Pan, X.P.[Xi-Peng], Zhao, W.[Wenyi], Li, C.Y.[Chong-Yi],
Underwater Image Enhancement via Weighted Wavelet Visual Perception Fusion,
CirSysVideo(34), No. 4, April 2024, pp. 2469-2483.
IEEE DOI Code:
WWW Link. 2404
Image color analysis, Image enhancement, Image restoration, Attenuation, Visual perception, Distortion, Degradation, underwater imaging BibRef

Zheng, Y.C.[Yu-Chao], Lu, H.M.[Hui-Min], Wang, J.Y.[Jing-Yi], Zhang, W.D.[Wei-Dong], Guizani, M.[Mohsen],
High-Turbidity Underwater Image Enhancement via Turbidity Suppression Fusion,
CirSysVideo(35), No. 4, April 2025, pp. 3527-3540.
IEEE DOI 2504
Image color analysis, Turbidity, Imaging, Image restoration, Histograms, Adaptation models, Computational modeling, contrast enhancement BibRef

Zhang, W.D.[Wei-Dong], Liu, Q.M.[Qing-Min], Feng, Y.K.[Yi-Kun], Cai, L.[Lei], Zhuang, P.X.[Pei-Xian],
Underwater Image Enhancement via Principal Component Fusion of Foreground and Background,
CirSysVideo(34), No. 11, November 2024, pp. 10930-10943.
IEEE DOI Code:
WWW Link. 2412
Image color analysis, Principal component analysis, Imaging, Visual perception, principal component fusion BibRef

Mu, D.L.[De-Lang], Li, H.[Heng], Liu, H.[Hui], Dong, L.[Ling], Zhang, G.Y.[Guo-Yin],
Underwater Image Enhancement Using a Mixed Generative Adversarial Network,
IET-IPR(17), No. 4, 2023, pp. 1149-1160.
DOI Link 2303
generative adversarial network, underwater images, visual perception enhancement BibRef

Li, M.Y.[Meng-Yao], Shen, L.Q.[Li-Quan], Lin, Y.F.[Yu-Fei], Wang, K.[Kun], Chen, J.[Jinbo],
Extreme Underwater Image Compression Using Physical Priors,
CirSysVideo(33), No. 4, April 2023, pp. 1937-1951.
IEEE DOI 2304
Image coding, Bit rate, Image reconstruction, Image color analysis, Wavelet transforms, Feature extraction, Codecs, conditional generator adversarial network (cGAN) BibRef

Peng, L.T.[Lin-Tao], Zhu, C.L.[Chun-Li], Bian, L.H.[Li-Heng],
U-Shape Transformer for Underwater Image Enhancement,
IP(32), 2023, pp. 3066-3079.
IEEE DOI 2306
BibRef
Earlier: AIM22(290-307).
Springer DOI 2304
Image color analysis, Visualization, Imaging, Circuit faults, Attenuation, Transformers, Task analysis, underwater image dataset BibRef

Hao, X.[Xuyan], Liu, L.X.[Li-Xin],
DGC-UWnet: Underwater image enhancement based on computation-efficient convolution and channel shuffle,
IET-IPR(17), No. 7, 2023, pp. 2158-2167.
DOI Link 2305
image enhancement, image processing BibRef

Fang, Z.K.[Zheng-Kai], Shen, L.Q.[Li-Quan], Li, M.Y.[Meng-Yao], Wang, Z.Y.[Zheng-Yong], Jin, Y.L.[Yan-Liang],
Prior-Guided Contrastive Image Compression for Underwater Machine Vision,
CirSysVideo(33), No. 6, June 2023, pp. 2950-2961.
IEEE DOI 2306
Image coding, Feature extraction, Machine vision, Task analysis, Degradation, Image reconstruction, Image recognition, contrastive learning BibRef

Li, K.Q.[Kun-Qian], Wu, L.[Li], Qi, Q.[Qi], Liu, W.J.[Wen-Jie], Gao, X.[Xiang], Zhou, L.Q.[Li-Qin], Song, D.L.[Da-Lei],
Beyond Single Reference for Training: Underwater Image Enhancement via Comparative Learning,
CirSysVideo(33), No. 6, June 2023, pp. 2561-2576.
IEEE DOI 2306
Training, Image enhancement, Visualization, Task analysis, Generators, Deep learning, Oceans, Underwater image enhancement, blind image quality assessment BibRef

Gao, S.[Shuaibo], Wu, W.H.[Wen-Hui], Li, H.[Hua], Zhu, L.W.[Lin-Wei], Wang, X.[Xu],
Atmospheric Scattering Model Induced Statistical Characteristics Estimation for Underwater Image Restoration,
SPLetters(30), 2023, pp. 658-662.
IEEE DOI 2306
Image restoration, Image color analysis, Atmospheric modeling, Estimation, Feature extraction, Convolutional neural networks, convolutional neural network BibRef

Wang, N.[Ning], Chen, T.[Tingkai], Kong, X.J.[Xiang-Jun], Chen, Y.Z.[Yan-Zheng], Wang, R.F.[Rong-Feng], Gong, Y.J.[Yong-Jun], Song, S.[Shiji],
Underwater Attentional Generative Adversarial Networks for Image Enhancement,
HMS(53), No. 3, June 2023, pp. 490-500.
IEEE DOI 2306
Image restoration, Image color analysis, Feature extraction, Task analysis, Image enhancement, Man-machine systems, underwater image enhancement (UIE) BibRef

Du, L.[Libin], Li, H.[Huming], Wang, L.[Lei], Lin, X.[Xu], Lv, Z.C.[Zhi-Chao],
Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference,
RS(15), No. 13, 2023, pp. 3222.
DOI Link 2307
BibRef

Honnutagi, P.[Pooja], Laitha, Y.S., Mytri, V.D.,
Underwater Video Enhancement Using Manta Ray Foraging Lion Optimization-Based Fusion Convolutional Neural Network,
IJIG(23), No. 4 2023, pp. 2350031.
DOI Link 2308
BibRef

Wang, Q.[Qiang], Fu, B.[Bo], Fan, H.J.[Hui-Jie],
Underwater image enhancement via a channel-wise transmission estimation network,
IET-IPR(17), No. 10, 2023, pp. 2958-2971.
DOI Link 2308
image enhancement, image restoration, image representation BibRef

Li, M.Y.[Meng-Yao], Wang, K.[Kun], Shen, L.Q.[Li-Quan], Lin, Y.F.[Yu-Fei], Wang, Z.Y.[Zheng-Yong], Zhao, Q.J.[Qi-Jie],
UIALN: Enhancement for Underwater Image With Artificial Light,
CirSysVideo(33), No. 8, August 2023, pp. 3622-3637.
IEEE DOI 2308
Image color analysis, Image enhancement, Lighting, Image restoration, Imaging, Distortion, Training, artificial light BibRef

Gonzalez-Sabbagh, S.P.[Salma P.], Robles-Kelly, A.[Antonio],
A Survey on Underwater Computer Vision,
Surveys(55), No. 13s, July 2023, pp. xx-yy.
DOI Link 2309
Survey, Underwater Vision. underwater image restoration, Underwater computer vision, underwater image formation models, underwater image enhancement BibRef

Cong, R.M.[Run-Min], Yang, W.Y.[Wen-Yu], Zhang, W.[Wei], Li, C.Y.[Chong-Yi], Guo, C.L.[Chun-Le], Huang, Q.M.[Qing-Ming], Kwong, S.[Sam],
PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN With Dual-Discriminators,
IP(32), 2023, pp. 4472-4485.
IEEE DOI 2309
BibRef

Nnolim, U.A.[Uche A.],
Fourth-Order Partial Differential Equation Framelet Fusion-Based Colour Correction and Contrast Enhancement for Underwater Images,
IJIG(23), No. 5 2023, pp. 2350044.
DOI Link 2310
BibRef

Cheng, N.[Na], Sun, Z.X.[Zhi-Xuan], Zhu, X.B.[Xuan-Bing], Wang, H.Y.[Hong-Yu],
A transformer-based network for perceptual contrastive underwater image enhancement,
SP:IC(118), 2023, pp. 117032.
Elsevier DOI 2310
Underwater image enhancement, Transformer, Multi-loss function, Contrastive learning BibRef

Lu, S.Q.[Si-Qi], Guan, F.X.[Feng-Xu], Zhang, H.Y.[Han-Yu], Lai, H.T.[Hai-Tao],
Underwater image enhancement method based on denoising diffusion probabilistic model,
JVCIR(96), 2023, pp. 103926.
Elsevier DOI 2310
Denoising diffusion probabilistic model (DDPM), Underwater image enhancement, Deep learning, Underwater image restoration BibRef

Liu, K.[Ke], Liang, Y.Q.[Yong-Quan],
Enhancement method for non-uniform scattering images of turbid underwater based on neural network,
IVC(138), 2023, pp. 104813.
Elsevier DOI 2310
Visual quality enhancement, Underwater optical image, Background light, Convolutional neural network, Image enhancement BibRef

Zhuang, L.[Lihao], Shen, L.Q.[Li-Quan], Wang, Z.Y.[Zheng-Yong], Li, Y.[Yinyi],
UCSNet: Priors Guided Adaptive Compressive Sensing Framework for Underwater Images,
CirSysVideo(33), No. 10, October 2023, pp. 5587-5604.
IEEE DOI 2310
BibRef

Qiao, N.Z.[Nian-Zu], Sun, J.[Jia], Ge, Q.B.[Quan-Bo], Sun, C.Y.[Chang-Yin],
UIE-FSMC: Underwater Image Enhancement Based on Few-Shot Learning and Multi-Color Space,
CirSysVideo(33), No. 10, October 2023, pp. 5391-5405.
IEEE DOI 2310
BibRef

Ma, H.P.[Hai-Ping], Sun, S.Y.[Sheng-Yi], Ye, S.G.[Seng-Gang], Jiang, Z.H.[Zhe-Heng],
Non-Uniform Illumination Underwater Image Enhancement via Minimum Weighted Error Entropy Loss,
SPLetters(30), 2023, pp. 1187-1191.
IEEE DOI 2310
BibRef

Yan, S.[Shuaizheng], Chen, X.Y.[Xing-Yu], Wu, Z.X.[Zheng-Xing], Tan, M.[Min], Yu, J.Z.[Jun-Zhi],
HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration,
IP(32), 2023, pp. 5004-5016.
IEEE DOI 2310
BibRef

Liu, Q.[Qiong], Zhang, Q.[Qi], Liu, W.[Wei], Chen, W.[Wenbai], Liu, X.W.[Xin-Wang], Wang, X.[Xiangke],
WSDS-GAN: A weak-strong dual supervised learning method for underwater image enhancement,
PR(143), 2023, pp. 109774.
Elsevier DOI 2310
Underwater image enhancement, Two-stage learning, Deep learning, CycleGAN BibRef

Lin, Z.[Zaifa], Shangguan, M.J.[Ming-Jia], Cao, F.Q.[Fu-Qing], Yang, Z.F.[Zhi-Feng], Qiu, Y.[Ying], Weng, Z.[Zhenwu],
Underwater Single-Photon Lidar Equipped with High-Sampling-Rate Multi-Channel Data Acquisition System,
RS(15), No. 21, 2023, pp. 5216.
DOI Link 2311
BibRef

Guo, P.F.[Peng-Fei], Liu, H.T.[Han-Tao], Zeng, D.[Delu], Xiang, T.[Tao], Li, L.[Leida], Gu, K.[Ke],
An Underwater Image Quality Assessment Metric,
MultMed(25), 2023, pp. 5093-5106.
IEEE DOI 2311
BibRef

Deng, R.[Ruhui], Zhao, L.[Lei], Li, H.[Heng], Liu, H.[Hui],
Cformer: An underwater image enhancement hybrid network combining convolution and transformer,
IET-IPR(17), No. 13, 2023, pp. 3841-3855.
DOI Link 2311
image enhancement, image processing BibRef

Zhang, S.Q.[Si-Qi], Li, Y.X.[Yu-Xuan], Tan, L.[Lu], Yang, H.[Huan], Hou, G.J.[Guo-Jia],
A no-reference underwater image quality evaluator via quality-aware features,
JVCIR(97), 2023, pp. 103979.
Elsevier DOI 2312
Underwater image, No-reference image quality assessment, Quality-aware features, Gaussian process regression BibRef

Avola, D.[Danilo], Cannistraci, I.[Irene], Cascio, M.[Marco], Cinque, L.[Luigi], Diko, A.[Anxhelo], Distante, D.[Damiano], Foresti, G.L.[Gian Luca], Mecca, A.[Alessio], Scagnetto, I.[Ivan],
Real-time GAN-based Model for Underwater Image Enhancement,
CIAP23(I:412-423).
Springer DOI 2312
BibRef

Tang, Y.H.[Yong-Hua], Liu, X.[Xu], Zhang, Z.P.[Zhi-Peng], Lin, S.[Sen],
Adaptive Underwater Image Enhancement Guided by Generalized Imaging Components,
SPLetters(30), 2023, pp. 1772-1776.
IEEE DOI 2312
BibRef

Zhang, X.D.[Xu-Dong], Cui, L.W.[Li-Wen], Fan, Z.G.[Zhi-Guo], Sun, R.[Rui], Li, Y.[Yang],
Multi-cues underwater image restoration algorithm combined with light field technology,
IET-IPR(17), No. 14, 2023, pp. 4116-4128.
DOI Link 2312
focusing, image restoration, light polarisation BibRef

Xue, X.W.[Xin-Wei], Ma, T.J.[Tian-Jiao], Han, Y.D.[Yi-Dong], Ma, L.[Long], Liu, R.S.[Ri-Sheng],
Learning Deep Scene Curve for Fast and Robust Underwater Image Enhancement,
SPLetters(31), 2024, pp. 6-10.
IEEE DOI 2401
BibRef

Gonzalez-Sabbagh, S.[Salma], Robles-Kelly, A.[Antonio], Gao, S.[Shang],
DGD-cGAN: A dual generator for image dewatering and restoration,
PR(148), 2024, pp. 110159.
Elsevier DOI 2402
Underwater image restoration, Generative adversarial network, Deep learning BibRef

Liu, Y.[Yutao], Gu, K.[Ke], Cao, J.C.[Jing-Chao], Wang, S.Q.[Shi-Qi], Zhai, G.T.[Guang-Tao], Dong, J.Y.[Jun-Yu], Kwong, S.[Sam],
UIQI: A Comprehensive Quality Evaluation Index for Underwater Images,
MultMed(26), 2024, pp. 2560-2573.
IEEE DOI 2402
Image quality, Feature extraction, Image color analysis, Indexes, Predictive models, Colored noise, Visualization, Underwater image, statistical modeling BibRef

Liu, Q.[Qian], He, Z.X.[Zong-Xin], Zhang, D.[Dehuan], Zhang, W.S.[Wei-Shi], Lin, Z.[Zifan], Sohel, F.[Ferdous],
DRC: Chromatic aberration intensity priors for underwater image enhancement,
JVCIR(98), 2024, pp. 104065.
Elsevier DOI 2402
Aquaculture, Underwater image, Image enhancement, Depth estimation, Imaging model BibRef

Hu, S.T.[Shu-Teng], Cheng, Z.[Zheng], Fan, G.D.[Guo-Dong], Gan, M.[Min], Chen, C.L.P.[C.L. Philip],
Texture-aware and color-consistent learning for underwater image enhancement,
JVCIR(98), 2024, pp. 104051.
Elsevier DOI 2402
Underwater image enhancement, Texture-aware, Color-consistent, Feature decoupling BibRef

Song, W.[Wei], Shen, Z.H.[Zhi-Hao], Zhang, M.H.[Ming-Hua], Wang, Y.[Yan], Liotta, A.[Antonio],
A hierarchical probabilistic underwater image enhancement model with reinforcement tuning,
JVCIR(98), 2024, pp. 104052.
Elsevier DOI 2402
Underwater image enhancement, Hierarchical probabilistic model, Underwater environment BibRef

Chaurasia, D.[Dhiraj], Chhikara, P.[Prateek],
Sea-Pix-GAN: Underwater image enhancement using adversarial neural network,
JVCIR(98), 2024, pp. 104021.
Elsevier DOI 2402
Adversarial neural network, Deep learning, Image processing, Underwater imaging BibRef

Hou, G.J.[Guo-Jia], Li, N.[Nan], Zhuang, P.X.[Pei-Xian], Li, K.[Kunqian], Sun, H.[Haihan], Li, C.Y.[Chong-Yi],
Non-Uniform Illumination Underwater Image Restoration via Illumination Channel Sparsity Prior,
CirSysVideo(34), No. 2, February 2024, pp. 799-814.
IEEE DOI Code:
WWW Link. 2402
Lighting, Image color analysis, Image restoration, Imaging, Image quality, Estimation, Channel estimation, NUID BibRef

Wang, H.[Hao], Sun, S.X.[Shi-Xin], Ren, P.[Peng],
Underwater Color Disparities: Cues for Enhancing Underwater Images Toward Natural Color Consistencies,
CirSysVideo(34), No. 2, February 2024, pp. 738-753.
IEEE DOI Code:
WWW Link. 2402
Image color analysis, Image enhancement, Histograms, Adaptation models, Imaging, Technological innovation, Scattering, underwater image enhancement BibRef

Liao, H.G.[Hong-Gang], Jiang, N.F.[Nan-Feng], Chen, W.L.[Wei-Ling], Wei, H.A.[Hong-An], Zhao, T.S.[Tie-Song],
Distillation-Based Utility Assessment for Compacted Underwater Information,
SPLetters(31), 2024, pp. 481-485.
IEEE DOI 2402
Feature extraction, Image coding, Quality assessment, Databases, Transform coding, Predictive models, Image quality, distillation BibRef

Khandouzi, A.[Ali], Ezoji, M.[Mehdi],
Coarse-to-fine underwater image enhancement with lightweight CNN and attention-based refinement,
JVCIR(99), 2024, pp. 104068.
Elsevier DOI 2403
Underwater image enhancement, Deep learning, Image processing, Convolutional neural network, Attention module, Modified histogram equalization BibRef

Zhou, J.J.[Jia-Jia], Zhuang, J.B.[Jun-Bin], Zheng, Y.[Yan], Chang, Y.S.[Ya-Sheng], Mazhar, S.[Suleman],
HIFI-Net: A Novel Network for Enhancement to Underwater Optical Images,
SPLetters(31), 2024, pp. 885-889.
IEEE DOI 2404
Convolution, Wavelet transforms, Kernel, Convolutional neural networks, Frequency-domain analysis, underwater optical image BibRef

Jiang, Q.P.[Qiu-Ping], Kang, Y.Z.[Yao-Zu], Wang, Z.H.[Zhi-Hua], Ren, W.Q.[Wen-Qi], Li, C.Y.[Chong-Yi],
Perception-Driven Deep Underwater Image Enhancement Without Paired Supervision,
MultMed(26), 2024, pp. 4884-4897.
IEEE DOI 2404
Image color analysis, Training, Atmospheric modeling, Generative adversarial networks, Image enhancement, Measurement BibRef

Rao, Y.[Yuan], Liu, W.J.[Wen-Jie], Li, K.[Kunqian], Fan, H.[Hao], Wang, S.[Sen], Dong, J.Y.[Jun-Yu],
Deep Color Compensation for Generalized Underwater Image Enhancement,
CirSysVideo(34), No. 4, April 2024, pp. 2577-2590.
IEEE DOI Code:
WWW Link. 2404
Image color analysis, Visualization, Probabilistic logic, Integrated circuit modeling, Degradation, Channel estimation, visual 3D reconstruction BibRef

Xue, C.[Chang], Liu, Q.Y.[Qing-Yu], Huang, Y.F.[Yi-Fan], Cheng, E.[En], Yuan, F.[Fei],
A Dual-Branch Autoencoder Network for Underwater Low-Light Polarized Image Enhancement,
RS(16), No. 7, 2024, pp. 1134.
DOI Link 2404
BibRef

Vlachos, M.[Marinos], Skarlatos, D.[Dimitrios],
Self-Adaptive Colour Calibration of Deep Underwater Images Using FNN and SfM-MVS-Generated Depth Maps,
RS(16), No. 7, 2024, pp. 1279.
DOI Link 2404
BibRef

Ouyang, W.J.[Wen-Jia], Liu, J.[Junnan], Wei, Y.H.[Yan-Hui],
An Underwater Image Enhancement Method Based on Balanced Adaption Compensation,
SPLetters(31), 2024, pp. 1034-1038.
IEEE DOI 2405
Image reconstruction, Attenuation, Semantics, Correlation, Image color analysis, Image enhancement, Optical imaging, underwater image enhancement BibRef

Liu, Y.[Yutao], Zhang, B.[Baochao], Hu, R.[Runze], Gu, K.[Ke], Zhai, G.T.[Guang-Tao], Dong, J.Y.[Jun-Yu],
Underwater Image Quality Assessment: Benchmark Database and Objective Method,
MultMed(26), 2024, pp. 7734-7747.
IEEE DOI 2405
Image quality, Databases, Imaging, Image color analysis, Transformers, Measurement, Degradation, Attention mechanism, underwater image BibRef

Zhou, J.C.[Jing-Chun], Wang, S.Y.[Shi-Yin], Lin, Z.[Zifan], Jiang, Q.P.[Qiu-Ping], Sohel, F.[Ferdous],
A Pixel Distribution Remapping and Multi-Prior Retinex Variational Model for Underwater Image Enhancement,
MultMed(26), 2024, pp. 7838-7849.
IEEE DOI 2405
Image color analysis, Lighting, Reflectivity, Attenuation, Brightness, Imaging, Colored noise, Underwater image enhancement, underwater prior knowledge BibRef

Liu, Z.K.[Zhen-Kai], Fu, X.X.[Xin-Xiao], Lin, C.[Chi], Xu, H.Y.[Hai-Yong],
COC-UFGAN: Underwater image enhancement based on color opponent compensation and dual-subnet underwater fusion generative adversarial network,
JVCIR(100), 2024, pp. 104101.
Elsevier DOI 2405
Underwater Image Enhancement, Color Opponent Compensation, Generative Adversarial Network BibRef

Lu, S.Q.[Si-Qi], Guan, F.X.[Feng-Xu], Zhang, H.Y.[Han-Yu], Lai, H.T.[Hai-Tao],
Speed-Up DDPM for Real-Time Underwater Image Enhancement,
CirSysVideo(34), No. 5, May 2024, pp. 3576-3588.
IEEE DOI 2405
Task analysis, Image color analysis, Image enhancement, Noise reduction, Mathematical models, Real-time systems, Lighting, deep learning BibRef

Wang, M.J.[Ming-Jie], Zhang, K.[Keke], Wei, H.A.[Hong-An], Chen, W.L.[Wei-Ling], Zhao, T.S.[Tie-Song],
Underwater image quality optimization: Researches, challenges, and future trends,
IVC(146), 2024, pp. 104995.
Elsevier DOI 2405
Underwater image enhancement, Underwater image restoration, Image quality assessment, Underwater image datasets BibRef

Li, Y.[Yinyi], Shen, L.Q.[Li-Quan], Li, M.Y.[Meng-Yao], Wang, Z.Y.[Zheng-Yong], Zhuang, L.[Lihao],
RUIESR: Realistic Underwater Image Enhancement and Super Resolution,
CirSysVideo(34), No. 6, June 2024, pp. 4713-4728.
IEEE DOI 2406
Degradation, Image color analysis, Superresolution, Task analysis, Image reconstruction, Distortion, Image enhancement, color casts BibRef

Huang, Y.[Yong], Chen, R.[Renzhang],
Scientific mapping and bibliometric analysis of research advancements in underwater image enhancement,
JVCIR(101), 2024, pp. 104166.
Elsevier DOI 2406
Underwater image enhancement, Deep learning, Underwater image restoration, Underwater image fusion, Underwater image denoising BibRef

Ma, L.P.[Lun-Peng], Hong, D.Y.[Dong-Yang], Yin, S.B.[Shi-Bai], Deng, W.Q.[Wan-Qiu], Yang, Y.[Yang], Yang, Y.H.[Yee-Hong],
Convolution-transformer blend pyramid network for underwater image enhancement,
JVCIR(101), 2024, pp. 104163.
Elsevier DOI 2406
Image enhancement, Laplacian pyramid, Convolutional neural network, Transformer, Wavelet transform BibRef

Li, F.[Fei], Zheng, J.B.[Jiang-Bin], Wang, L.[Lu], Wang, S.[Shengkang],
Integrating Cross-Domain Feature Representation and Semantic Guidance for Underwater Image Enhancement,
SPLetters(31), 2024, pp. 1511-1515.
IEEE DOI 2406
Semantics, Feature extraction, Image enhancement, Image color analysis, Image restoration, Visualization, underwater image enhancement BibRef

Lu, S.Q.[Si-Qi], Guan, F.X.[Feng-Xu], Lai, H.T.[Hai-Tao],
Underwater image enhancement based on global features and prior distribution guided,
IVC(148), 2024, pp. 105101.
Elsevier DOI 2407
Underwater image enhancement, Global features, Generalization capabilities, Condition variational auto-encoder BibRef

Li, M.Y.[Meng-Yao], Shen, L.Q.[Li-Quan], Hua, X.[Xia], Tian, Z.[Zhaoyi],
EUICN: An Efficient Underwater Image Compression Network,
CirSysVideo(34), No. 7, July 2024, pp. 6474-6488.
IEEE DOI 2407
Image coding, Imaging, Feature extraction, Correlation, Quantization (signal), Entropy coding, Oceans, entropy model BibRef

Wang, H.[Hao], Zhang, W.[Weibo], Ren, P.[Peng],
Self-organized underwater image enhancement,
PandRS(215), 2024, pp. 1-14.
Elsevier DOI Code:
WWW Link. 2408
Self-organized, Underwater image enhancement, Human visual perception, Underwater color prior, Reinforcement learning BibRef

Li, P.T.[Pei-Tong], Chen, J.Y.[Jia-Ying], Cai, C.T.[Cheng-Tao],
Reinforced Res-Unet transformer for underwater image enhancement,
SP:IC(127), 2024, pp. 117154.
Elsevier DOI 2408
Underwater image enhancement, Deep residual network, Convolutional neural network, Vision transformer, Underwater image synthesis BibRef

Kumar, K.P.[Kattela Pavan], Rao, M.V.G.[Matcha Venu Gopala], Venkatanarayana, M.[Moram],
A Novel Image Recovery from Moving Water Surface Using Multi-Objective Bispectrum Method,
IJIG(24), No. 4, July 2024, pp. 2450038.
DOI Link 2408
BibRef

Lin, Z.Q.[Zhi-Qiang], He, Z.[Zhouyan], Jin, C.[Chongchong], Luo, T.[Ting], Chen, Y.[Yeyao],
Joint Luminance-Saliency Prior and Attention for Underwater Image Quality Assessment,
RS(16), No. 16, 2024, pp. 3021.
DOI Link 2408
BibRef

Zhou, J.C.[Jing-Chun], Chen, S.H.[Shu-Han], Zhang, D.[Dehuan], He, Z.X.[Zong-Xin], Lam, K.M.[Kin-Man], Sohel, F.[Ferdous], Vivone, G.[Gemine],
Adaptive variational decomposition for water-related optical image enhancement,
PandRS(216), 2024, pp. 15-31.
Elsevier DOI 2408
Underwater image, Underwater image enhancement, Backward scattering, Variational method BibRef

Qiao, N.Z.[Nian-Zu], Sun, C.Y.[Chang-Yin], Dong, L.[Lu], Ge, Q.B.[Quan-Bo],
Semi-Supervised Feature Distillation and Unsupervised Domain Adversarial Distillation for Underwater Image Enhancement,
CirSysVideo(34), No. 8, August 2024, pp. 7671-7682.
IEEE DOI 2408
Image enhancement, Knowledge engineering, Training, Image color analysis, Deep learning, Histograms, Degradation, alternate training BibRef

Hao, S.Y.[Shu-Yu], Guo, J.[Jichang], An, G.H.[Guan-Hua], Wang, Y.D.[Yu-Dong],
Underwater image enhancement via multicolor space-guided curve estimation,
JVCIR(103), 2024, pp. 104240.
Elsevier DOI 2409
Underwater image enhancement, Deep learning, Multiple color spaces, Nonlinear mapping BibRef

Chen, B.Y.[Bing-Yuan], Su, J.N.[Jian-Nan], Chen, G.Y.[Guang-Yong], Gan, M.[Min],
FISTA acceleration inspired network design for underwater image enhancement,
JVCIR(103), 2024, pp. 104224.
Elsevier DOI 2409
Underwater image enhancement, FISTA algorithm, Proximal gradient, Deep learning BibRef

Wang, Z.Y.[Zheng-Yong], Shen, L.Q.[Li-Quan], Yu, Y.[Yihan], Hui, Y.[Yuan],
UIERL: Internal-External Representation Learning Network for Underwater Image Enhancement,
MultMed(26), 2024, pp. 9252-9267.
IEEE DOI 2409
Image enhancement, Representation learning, Task analysis, Visualization, Optical fibers, Image segmentation, underwater image enhancement BibRef

Li, J.R.[Jian-Ru], Zhu, X.[Xu], Zheng, Y.C.[Yu-Chao], Lu, H.M.[Hui-Min], Li, Y.J.[Yu-Jie],
Underwater image restoration based on light attenuation prior and color-contrast adaptive correction,
IVC(150), 2024, pp. 105217.
Elsevier DOI 2409
Underwater image restoration, Attenuation ratio, Adaptive color-contrast correction BibRef

An, S.M.[Shun-Min], Xu, L.H.[Li-Hong], Deng, Z.C.[Zhi-Chao],
FastUNet: Fast hierarchical multi-patch underwater enhancement network for industrial recirculating aquaculture,
PR(157), 2025, pp. 110928.
Elsevier DOI 2409
Recirculating aquaculture, Hierarchical multi-patch, Prior constraint, Underwater enhancement BibRef

An, G.H.[Guan-Hua], He, A.[Ao], Wang, Y.D.[Yu-Dong], Guo, J.C.[Ji-Chang],
UWMamba: UnderWater Image Enhancement With State Space Model,
SPLetters(31), 2024, pp. 2725-2729.
IEEE DOI 2410
Convolution, Feature extraction, Image enhancement, Visualization, Image color analysis, Fuses, Computational modeling, underwater image enhancement BibRef

Zhou, J.C.[Jing-Chun], Sun, J.M.[Jia-Ming], Li, C.Y.[Chong-Yi], Jiang, Q.P.[Qiu-Ping], Zhou, M.[Man], Lam, K.M.[Kin-Man], Zhang, W.S.[Wei-Shi], Fu, X.P.[Xian-Ping],
HCLR-Net: Hybrid Contrastive Learning Regularization with Locally Randomized Perturbation for Underwater Image Enhancement,
IJCV(132), No. 10, October 2024, pp. 4132-4156.
Springer DOI 2410
BibRef
And: Correction: IJCV(132), No. 11, November 2024, pp. 5490-5490.
Springer DOI 2411
BibRef

Liu, Y.[Yi], Jiang, Q.P.[Qiu-Ping], Wang, X.[Xinyi], Luo, T.[Ting], Zhou, J.C.[Jing-Chun],
Underwater Image Enhancement with Cascaded Contrastive Learning,
MultMed(27), 2025, pp. 1512-1525.
IEEE DOI 2503
Image color analysis, Contrastive learning, Degradation, Training, Lower bound, Deep learning, Visualization, Image enhancement, contrastive learning BibRef

Ji, X.[Xun], Wang, X.[Xu], Leng, N.[Na], Hao, L.Y.[Li-Ying], Guo, H.[Hui],
Dual-branch underwater image enhancement network via multiscale neighborhood interaction attention learning,
IVC(151), 2024, pp. 105256.
Elsevier DOI 2411
Underwater image enhancement, Convolutional neural network, Deep learning, Attention mechanism BibRef

Zhu, J.C.[Jia-Cheng], Wen, J.J.[Jun-Jie], Hong, D.[Duanqin], Lin, Z.P.[Zhan-Peng], Hong, W.X.[Wen-Xing],
UIR-ES: An unsupervised underwater image restoration framework with equivariance and stein unbiased risk estimator,
IVC(151), 2024, pp. 105285.
Elsevier DOI 2411
Underwater image restoration, Unsupervised learning, Equivariance, Stein unbiased risk estimator BibRef

Hao, Y.S.[Yan-Sheng], Yuan, Y.Y.[Yao-Yao], Zhang, H.[Hongman], Zhang, Z.[Ze],
Underwater Optical Imaging: Methods, Applications and Perspectives,
RS(16), No. 20, 2024, pp. 3773.
DOI Link 2411
BibRef

Li, Y.Y.[Yuan-Yuan], Mi, Z.[Zetian], Lin, P.[Peng], Fu, X.P.[Xian-Ping],
Underwater image enhancement via brightness mask-guided multi-attention embedding,
SP:IC(130), 2025, pp. 117200.
Elsevier DOI 2412
Underwater image enhancement, Brightness mask-guided, Attention mechanism, Deep learning BibRef

González-Sabbagh, S.[Salma], Robles-Kelly, A.[Antonio], Gao, S.[Shang],
Scene-cGAN: A GAN for underwater restoration and scene depth estimation,
CVIU(250), 2025, pp. 104225.
Elsevier DOI 2501
Generative adversarial network, Underwater image restoration, Underwater scene depth estimation BibRef

Song, J.Y.[Jing-Yu], Xu, H.Y.[Hai-Yong], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Chen, Y.[Yeyao], Luo, T.[Ting], Song, Y.[Yang],
Frequency domain-based latent diffusion model for underwater image enhancement,
PR(160), 2025, pp. 111198.
Elsevier DOI 2501
Frequency domain, Latent diffusion model, Underwater image enhancement BibRef

Xia, H.S.[Hai-Sheng], Bao, B.L.[Bing-Lei], Liao, F.[Fei], Chen, J.T.[Jin-Tao], Wang, B.L.[Bing-Lu], Li, Z.J.[Zhi-Jun],
A Patch-Based Method for Underwater Image Enhancement With Denoising Diffusion Models,
Cyber(55), No. 1, January 2025, pp. 269-281.
IEEE DOI 2501
Image restoration, Diffusion models, Noise, Noise reduction, Image resolution, Training, Spatial resolution, underwater image enhancement (UIE) BibRef

Zhou, Y.[Yang], Su, Q.H.[Qing-Hua], Hu, Z.[Zhongbo], Jiang, S.J.[Shao-Jie],
Underwater image enhancement method via extreme enhancement and ultimate weakening,
JVCIR(105), 2024, pp. 104341.
Elsevier DOI 2501
Contrast balance, Extreme enhancement, Grey prediction evolution algorithm, Pure gray image, Underwater image enhancement BibRef

Wei, T.Y.[Tian-Yu], Zhang, D.H.[De-Huan], He, Z.X.[Zong-Xin], Zhou, R.[Rui], Meng, X.F.[Xiang-Fu],
Multi-domain conditional prior network for water-related optical image enhancement,
CVIU(251), 2025, pp. 104251.
Elsevier DOI 2501
Computational photography, Underwater imaging, Water-related optical images, Image enhancement BibRef

Xia, H.S.[Hai-Sheng], Liao, F.[Fei], Bao, B.L.[Bing-Lei], Chen, J.T.[Jin-Tao], Wang, B.[Binglu], Huang, Q.H.[Qing-Hua], Li, Z.J.[Zhi-Jun],
Perspective on Wearable Systems for Human Underwater Perceptual Enhancement,
Cyber(55), No. 2, February 2025, pp. 698-711.
IEEE DOI 2502
Biomedical monitoring, Sensors, Visualization, Wearable devices, Underwater navigation, Sonar, Global Positioning System, virtual reality BibRef

Jiang, Q.P.[Qiu-Ping], Yi, X.[Xiao], Ouyang, L.[Li], Zhou, J.C.[Jing-Chun], Wang, Z.H.[Zhi-Hua],
Toward Dimension-Enriched Underwater Image Quality Assessment,
CirSysVideo(35), No. 2, February 2025, pp. 1385-1398.
IEEE DOI Code:
WWW Link. 2502
Image color analysis, Image quality, Measurement, Benchmark testing, Annotations, Degradation, Feature extraction, bidirectional feature aggregation BibRef

Cheng, Z.[Zheng], Fan, G.D.[Guo-Dong], Zhou, J.C.[Jing-Chun], Gan, M.[Min], Chen, C.L.P.[C. L. Philip],
FDCE-Net: Underwater Image Enhancement With Embedding Frequency and Dual Color Encoder,
CirSysVideo(35), No. 2, February 2025, pp. 1728-1744.
IEEE DOI Code:
WWW Link. 2502
Image color analysis, Colored noise, Image enhancement, Degradation, Imaging, Histograms, Frequency-domain analysis, transformer BibRef

Zhuang, J.B.[Jun-Bin], Zheng, Y.[Yan], Guo, B.[Baolong], Yan, Y.[Yunyi],
Globally Deformable Information Selection Transformer for Underwater Image Enhancement,
CirSysVideo(35), No. 1, January 2025, pp. 19-32.
IEEE DOI 2502
Transformers, Image color analysis, Image enhancement, Image processing, Circuit faults, Feature extraction, global feature selection BibRef

Li, Y.Y.[Yuan-Yuan], Mi, Z.[Zetian], Wang, Y.L.[Yu-Lin], Jiang, S.[Shuaiyong], Fu, X.P.[Xian-Ping],
TAFormer: A Transmission-Aware Transformer for Underwater Image Enhancement,
CirSysVideo(35), No. 1, January 2025, pp. 601-616.
IEEE DOI 2502
Imaging, Transformers, Image color analysis, Image enhancement, Image restoration, Degradation, Circuit faults, underwater image enhancement BibRef

Xu, X.Y.[Xiao-Yi], Cai, H.[Hui], Wang, M.J.[Ming-Jie], Chen, W.L.[Wei-Ling], Zhang, R.X.[Rong-Xin], Zhao, T.S.[Tie-Song],
Exploring underwater image quality: A review of current methodologies and emerging trends,
IVC(154), 2025, pp. 105389.
Elsevier DOI 2502
Underwater image quality, Underwater optical image, Sonar image, Subjective quality assessment, Objective quality assessment BibRef

Shao, J.X.[Jin-Xin], Zhang, H.[Haosu], Miao, J.M.[Jian-Ming],
GPLM: Enhancing underwater images with Global Pyramid Linear Modulation,
IVC(154), 2025, pp. 105361.
Elsevier DOI 2502
Underwater image enhancement, Global Pyramid Linear Modulation (GPLM), Real world underwater enhancement dataset BibRef

Yao, J.R.[Jin-Ren], Elamassie, M.[Mohammed], Korotkova, O.[Olga],
Spatial power spectrum of natural water turbulence with any average temperature, salinity concentration, and light wavelength,
JOSA-A(37), No. 10, October 2020, pp. 1614-1621.
DOI Link 2503
Light propagation, Optical turbulence, Refractive index, Salinity, Scintillation index, Signal transmission BibRef

Ata, Y.[Yalcin], Korotkova, O.[Olga],
Adaptive optics correction in natural turbulent waters,
JOSA-A(38), No. 4, April 2021, pp. 587-594.
DOI Link 2503
Adaptive optics, Laser communications, Oceanic turbulence, Refractive index, Scintillation index, Spatial filtering BibRef

Chen, Y.H.[Yong-Hao], Liu, X.Y.[Xiao-Yun], Jiang, J.Y.[Jin-Yang], Gao, S.[Siyu], Liu, Y.[Ying], Jiang, Y.[Yueqiu],
Reconstruction of degraded image transmitting through ocean turbulence via deep learning,
JOSA-A(40), No. 12, December 2023, pp. 2215-2222.
DOI Link 2503
Computational imaging, Deep learning, Laser beam propagation, Laser imaging, Neural networks, Optical imaging BibRef

Zhao, G.Q.[Guo-Qing], Zhang, Y.X.[Yi-Xin], Yan, Q.Z.[Qing-Ze], Yu, L.[Lin], Zhu, Y.[Yun], Hu, L.[Lifa],
Information propagation of focus wave mode localized waves in anisotropic turbulent seawater,
JOSA-A(41), No. 6, June 2024, pp. B106-B115.
DOI Link 2503
Bit error rate, Mode division multiplexing, Optical signals, Optical systems, Optical transceivers, Wave propagation BibRef

Ferlic, N.A.[Nathaniel A.], Laux, A.E.[Alan E.], Mullen, L.J.[Linda J.],
Optical phase and amplitude measurements of underwater turbulence via self-heterodyne detection,
JOSA-A(41), No. 6, June 2024, pp. B95-B105.
DOI Link 2503
Heterodyne detection, Laser beams, Light propagation, Optical turbulence, Phase noise, Phase shift BibRef

Nair, A.[Anjali], Li, Q.[Qin], Stechmann, S.N.[Samuel N.],
Estimating the time-evolving refractivity of a turbulent medium using optical beam measurements: a data assimilation approach,
JOSA-A(41), No. 6, June 2024, pp. B73-B84.
DOI Link 2503
Computer simulation, Free space optics, Inverse design, Light beams, Optical signals, Refractive index BibRef

Deng, X.Y.[Xiang-Yu], Zhang, Y.Q.[Yong-Qing], Wang, H.[Huigang], Hu, H.[Hao],
Robust underwater image enhancement method based on natural light and reflectivity,
JOSA-A(38), No. 2, February 2021, pp. 181-191.
DOI Link 2503
Image enhancement, Image metrics, Imaging techniques, Neural networks, Point spread function, Underwater imaging BibRef

Zhang, Y.[Yingluo], Cheng, Q.[Qian], Zhang, Y.[Yike], Han, F.[Fei],
Image-restoration algorithm based on an underwater polarization imaging visualization model,
JOSA-A(39), No. 5, May 2022, pp. 855-865.
DOI Link 2503
Imaging systems, Imaging techniques, Laser imaging, Optical imaging, Polarimetric imaging, Underwater imaging BibRef

Liao, Z.D.[Zi-Dong], Lu, Z.[Zheng], Li, J.[Jian], Wang, Q.[Qin],
Robust 3D imaging based on regularization by denoising,
JOSA-A(39), No. 11, November 2022, pp. 2001-2008.
DOI Link 2503
Imaging techniques, Photon counting, Photon echoes, Three dimensional imaging, Underwater imaging, Wavelet transforms BibRef

Yang, J.[Junyi], Cai, M.[Mudan], Wang, C.[Chao], Zheng, M.[Minhui], Chen, S.[Sheng],
Underwater image illumination estimation via an evolving extreme learning machine by an improved salp swarm algorithm,
JOSA-A(40), No. 3, March 2023, pp. 560-572.
DOI Link 2503
Chromatic aberration, Image metrics, Light sources, Machine vision, Neural networks, Underwater imaging BibRef

Yang, X.L.[Xie-Liu], Li, J.P.[Jian-Ping], Liang, W.F.[Wen-Feng], Wang, D.[Dan], Zhao, J.B.[Jin-Bao], Xia, X.H.[Xiao-Hua],
Underwater image quality assessment,
JOSA-A(40), No. 7, July 2023, pp. 1276-1288.
DOI Link 2503
Image metrics, Image restoration, Imaging techniques, Neural networks, Physiology, Underwater imaging BibRef

Deng, X.Y.[Xiang-Yu], Zhu, K.[Kexin], Rong, S.W.[Shao-Wei],
Perceptual illumination-structure patch decomposition for enhancing complex lighted underwater images,
JOSA-A(41), No. 9, September 2024, pp. 1683-1692.
DOI Link 2503
Deep learning, Image metrics, Imaging techniques, Light sources, Machine vision, Underwater imaging BibRef

Lang, L.Y.[Li-Ying], Zhang, J.H.[Jing-Han], Feng, H.[Haoyi], Pang, Y.J.[Ya-Jun],
Research of the underwater polarization imaging process based on the Oren-Nayar polarization bidirectional reflection distribution function,
JOSA-A(41), No. 11, November 2024, pp. 2041-2053.
DOI Link 2503
Imaging systems, Imaging techniques, Laser imaging, Polarimetric imaging, Systems design, Underwater imaging BibRef

Quero, C.O.[Carlos Osorio], Rondon, I.[Irving], Martinez-Carranza, J.[Jose],
Improving NIR single-pixel imaging: using deep image prior and GANs,
JOSA-A(42), No. 2, February 2025, pp. 201-210.
DOI Link 2503
Ghost imaging, Neural networks, Single pixel imaging, Spatial light modulators, Three dimensional imaging, Underwater imaging BibRef

Liu, X.[Xiao], Liu, Z.W.[Zi-Wei], Yu, L.[Li],
Empower network to comprehend: Semantic guided and attention fusion GAN for underwater image enhancement,
SP:IC(134), 2025, pp. 117271.
Elsevier DOI 2503
Underwater image enhancement, GAN, Attention feature fusion BibRef

Nie, B.[Binyu], Lu, W.J.[Wen-Jie], Feng, Y.X.[Yun-Xuan], Gao, H.W.[Hao-Wen], Lin, K.Y.[Kai-Yang],
Removing multi-path echoes in underwater 3D reconstruction via multi-view consistency,
PRL(189), 2025, pp. 48-55.
Elsevier DOI Code:
WWW Link. 2503
Multi-path effect, Underwater perception, Multi-view consistency, Reconstruction BibRef

Wu, Z.[Zeju], Chen, K.M.[Kai-Ming], Ji, P.X.[Pan-Xin], Zhao, H.R.[Hao-Ran], Sun, X.[Xin],
MSFFT-Net: A multi-scale feature fusion transformer network for underwater image enhancement,
JVCIR(107), 2025, pp. 104355.
Elsevier DOI 2503
Underwater image enhancement, Deep learning, Window self-attention, Multi-scale feature fusion BibRef

Purnima, K.[Kuruma], Kumar, C.S.[C. Siva],
Devising a comprehensive synthetic underwater image dataset,
JVCIR(107), 2025, pp. 104386.
Elsevier DOI 2503
Backscatter, Color cast, Contrast reduction, Focus metric, Light attenuation, Underwater dataset BibRef

Jiang, Q.P.[Qiu-Ping], Gu, Y.[Yuese], Wu, Z.[Zongwei], Li, C.Y.[Chong-Yi], Xiong, H.[Huan], Shao, F.[Feng], Wang, Z.H.[Zhi-Hua],
Deep Underwater Image Quality Assessment With Explicit Degradation Awareness Embedding,
IP(34), 2025, pp. 1297-1310.
IEEE DOI Code:
WWW Link. 2503
Degradation, Training, Gray-scale, Image quality, Distortion, Decoding, Imaging, Image color analysis, Artificial neural networks, deep learning BibRef

Kapoor, M.[Meghna], Satya, B.N.[Bhargava N.], Subudhi, B.N.[Badri N.], Jakhetiya, V.[Vinit], Bansal, A.[Ankur],
Underwater surveillance using spatially curated perceptual loss and graph refactored network,
PR(162), 2025, pp. 111388.
Elsevier DOI 2503
Underwater surveillance, Graph convolution network, Underwater image enhancement BibRef

Ma, H.P.[Hai-Ping], Huang, J.Y.[Ji-Yuan], Shen, C.X.[Chen-Xu], Jiang, Z.H.[Zhe-Heng],
Retinex-inspired underwater image enhancement with information entropy smoothing and non-uniform illumination priors,
PR(162), 2025, pp. 111411.
Elsevier DOI 2503
Underwater image enhancement, Retinex variational model, Non-uniform illumination, Minimum weighted error entropy, Independent and piecewise identical distribution BibRef

Cao, J.Z.[Jiang-Zhong], Zeng, Z.[Zekai], Zhang, X.[Xu], Zhang, H.[Huan], Fan, C.L.[Chun-Ling], Jiang, G.Y.[Gang-Yi], Lin, W.S.[Wei-Si],
Unveiling the underwater world: CLIP perception model-guided underwater image enhancement,
PR(162), 2025, pp. 111395.
Elsevier DOI 2503
CLIP perception model, Underwater Image Enhancement, Curriculum contrastive regularization BibRef

Srinath, S.[Suhas], Chandrasekar, A.[Aditya], Jamadagni, H.[Hemang], Soundararajan, R.[Rajiv], P, P.A.[Prathosh A],
UnDIVE: Generalized Underwater Video Enhancement Using Generative Priors,
WACV25(9001-9012)
IEEE DOI 2505
Degradation, Computational modeling, Noise reduction, Imaging, Streaming media, Diffusion models, Real-time systems, temporal consistency BibRef

Mishra, P.[Priyanka], Mehta, N.[Nancy], Vipparthi, S.K.[Santosh Kumar], Murala, S.[Subrahmanyam],
USWformer: Efficient Sparse Wavelet Transformer for Underwater Image Enhancement,
WACV25(3372-3382)
IEEE DOI 2505
Wavelet transforms, Wavelet domain, Computational modeling, Frequency-domain analysis, Redundancy, Transformers, Image reconstruction BibRef

Khan, M.R.[Md Raqib], Negi, A.[Anshul], Kulkarni, A.[Ashutosh], Phutke, S.S.[Shruti S.], Vipparthi, S.K.[Santosh Kumar], Murala, S.[Subrahmanyam],
Phaseformer: Phase-Based Attention Mechanism for Underwater Image Restoration and Beyond,
WACV25(9618-9629)
IEEE DOI 2505
Degradation, Training, Attention mechanisms, Object detection, Feature extraction, Transformers, Image restoration, SQUIDs, Underwater Image Restoration BibRef

Azhar, A.S.B.M.[Amiera Syazlin Binti Md], Harun, N.H.B.[Nor Hazlyna Binti], Yusoff, N.B.[Nooraini Binti], Hassan, M.G.B.[Mohamad Ghozali Bin], Chu, K.B.[Kua Beng],
Image Enhancement on Underwater Images for Protozoan White Spot Fish Disease Detection,
ISCV22(1-4)
IEEE DOI 2208
Image quality, Economics, Histograms, Image color analysis, Fish, Intelligent systems, Image Enhancement BibRef

Lin, W.T.[Wei-Tung], Lin, Y.X.[Yong-Xiang], Chen, J.W.[Jyun-Wei], Hua, K.L.[Kai-Lung],
Pixmamba: Leveraging State Space Models in a Dual-level Architecture for Underwater Image Enhancement,
ACCV24(IV: 176-191).
Springer DOI 2412
BibRef

Nathan, O.B.[Opher Bar], Levy, D.[Deborah], Treibitz, T.[Tali], Rosenbaum, D.[Dan],
Osmosis: RGBD Diffusion Prior for Underwater Image Restoration,
ECCV24(LXII: 302-319).
Springer DOI 2412
BibRef

Sauder, J.[Jonathan], Tuia, D.[Devis],
Self-supervised Underwater Caustics Removal and Descattering via Deep Monocular SLAM,
ECCV24(LXXXIV: 214-232).
Springer DOI 2412
BibRef

Ikeda, T.[Takaki], Iwaguchi, T.[Takafumi], Thomas, D.[Diego], Kawasaki, H.[Hiroshi],
A Practical Calibration Method for Cameras and Multiple Line-Lasers in Light Sectioning Systems for Underwater Environments,
ICIP24(1602-1608)
IEEE DOI 2411
Laser theory, Solid modeling, Accuracy, Computational modeling, Measurement by laser beam, Laser modes, Underwater 3D scan, ROV, light-sectioning method BibRef

Tun, M.T.[May Thet], Sugiura, Y.[Yosuke], Shimamura, T.[Tetsuya],
Lightweight Underwater Image Enhancement via Impulse Response of Low-Pass Filter Based Attention Network,
ICIP24(1697-1703)
IEEE DOI 2411
Performance evaluation, Autonomous underwater vehicles, Visualization, Image coding, Convolution, Low-pass filters, SimAM attention module BibRef

Zhao, C.[Chen], Cai, W.L.[Wei-Ling], Dong, C.Y.[Chen-Yu], Hu, C.W.[Cheng-Wei],
Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration,
CVPR24(8281-8291)
IEEE DOI Code:
WWW Link. 2410
Degradation, Visualization, Wavelet domain, Codes, Frequency-domain analysis, Diffusion models, Fourier Information BibRef

Xie, Y.F.[Yao-Feng], Kong, L.W.[Ling-Wei], Chen, K.[Kai], Zheng, Z.Q.[Zi-Qiang], Yu, X.[Xiao], Yu, Z.B.[Zhi-Bin], Zheng, B.[Bing],
UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement,
CVPR24(22358-22367)
IEEE DOI 2410
Degradation, Training, Video sequences, Benchmark testing, Real-time systems, Kernel, video processing BibRef

Zhang, F.[Fan], You, S.[Shaodi], Li, Y.[Yu], Fu, Y.[Ying],
Atlantis: Enabling Underwater Depth Estimation with Stable Diffusion,
CVPR24(11852-11861)
IEEE DOI Code:
WWW Link. 2410
Training, Deep learning, Pipelines, Estimation, Lighting, Diffusion models, underwater depth estimation BibRef

Boittiaux, C.[Clémentin], Marxer, R.[Ricard], Dune, C.[Claire], Arnaubec, A.[Aurélien], Ferrera, M.[Maxime], Hugel, V.[Vincent],
SUCRe: Leveraging Scene Structure for Underwater Color Restoration,
3DV24(1488-1497)
IEEE DOI 2408
Image resolution, Codes, Image color analysis, Scattering, Distance measurement, Image restoration, Texturing BibRef

Chandrasekar, A.[Aditya], Sreenivas, M.[Manogna], Biswas, S.[Soma],
PhISH-Net: Physics Inspired System for High Resolution Underwater Image Enhancement,
WACV24(1495-1505)
IEEE DOI 2404
Water, Image color analysis, Computational modeling, Neural networks, Attenuation, Real-time systems, Algorithms, image and video synthesis BibRef

Khan, M.R.[Md Raqib], Mishra, P.[Priyanka], Mehta, N.[Nancy], Phutke, S.S.[Shruti S.], Vipparthi, S.K.[Santosh Kumar], Nandi, S.[Sukumar], Murala, S.[Subrahmanyam],
Spectroformer: Multi-Domain Query Cascaded Transformer Network For Underwater Image Enhancement,
WACV24(1443-1452)
IEEE DOI Code:
WWW Link. 2404
Codes, Image color analysis, Lighting, Estimation, Transformers, Distortion, Algorithms, Image recognition and understanding, Video recognition and understanding BibRef

Wang, Z.[Zhe], Yu, H.Y.[Hai-Yang], Peng, J.[Jin],
Underwater image recovery method considering target polarization characteristics,
CVIDL23(123-127)
IEEE DOI 2403
Parameter estimation, Optical polarization, Image color analysis, Filtering, Imaging, Manuals, Filtering algorithms, image enhancement BibRef

Li, X.[Xiang], Kou, Y.[Yejun], Liang, Y.C.[Yan-Chun],
Binocular Matching Method for Detecting and Locating Marine Resources Using Binocular Cameras and Deep Learning,
CVIDL23(381-384)
IEEE DOI 2403
Deep learning, Autonomous underwater vehicles, Target tracking, Heuristic algorithms, Robot vision systems, Neural networks, Underwater vision BibRef

Peng, J.[Jin], Yu, H.Y.[Hai-Yang], Wang, Z.[Zhe],
Underwater Image Color Analysis and Indicators Based on Statistical Characteristics,
CVIDL23(1-7)
IEEE DOI 2403
Water, Deep learning, Histograms, Image color analysis, Statistical analysis, Attenuation, qualitative and quantitative analysis BibRef

Rensen, T.[Tim], Green, R.[Richard],
Identifying Sources of Error in Underwater Photogrammetry via Sensitivity Analysis,
IVCNZ23(1-6)
IEEE DOI 2403
Systematics, Sensitivity analysis, Measurement uncertainty, Optical variables measurement, Cameras, sizing BibRef

Li, M.Y.[Meng-Yao], Shen, L.Q.[Li-Quan], Ye, P.[Peng], Feng, G.R.[Guo-Rui], Wang, Z.[Zheyin],
RFD-ECNet: Extreme Underwater Image Compression with Reference to Feature Dictionary,
ICCV23(12934-12943)
IEEE DOI 2401
BibRef

Kapoor, M.[Meghna], Baghel, R.[Rohan], Subudhi, B.N.[Badri Narayan], Jakhetiya, V.[Vinit], Bansal, A.[Ankur],
Domain Adversarial Learning Towards Underwater Image Enhancement,
WiCV-ICCV23(2233-2243)
IEEE DOI 2401
BibRef

Pham, T.T.[Thuy Thi], Mai, T.T.N.[Truong Thanh Nhat], Lee, C.[Chul],
Deep Unfolding Network with Physics-Based Priors for Underwater Image Enhancement,
ICIP23(46-50)
IEEE DOI 2312
BibRef

Chu, X.Y.[Xue-Ye], Fu, Z.Q.[Zhen-Qi], Yu, S.C.[Shao-Cong], Tu, X.T.[Xiao-Tong], Huang, Y.[Yue], Ding, X.H.[Xing-Hao],
Underwater Image Enhancement and Super-Resolution Using Implicit Neural Networks,
ICIP23(1295-1299)
IEEE DOI 2312
BibRef

Badran, M.[Mohamed], Torki, M.[Marwan],
DAUT: Underwater Image Enhancement Using Depth Aware U-shape Transformer,
ICIP23(1830-1834)
IEEE DOI Code:
WWW Link. 2312
BibRef

Jiang, J.X.[Jing-Xia], Bai, J.[Jinbin], Liu, Y.[Yun], Yin, J.J.[Jun-Jie], Chen, S.[Sixiang], Ye, T.[Tian], Chen, E.[Erkang],
RSFDM-Net: Real-Time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancement,
ICIP23(2560-2564)
IEEE DOI 2312
BibRef

Huang, S.R.[Shi-Rui], Wang, K.[Keyan], Liu, H.[Huan], Chen, J.[Jun], Li, Y.S.[Yun-Song],
Contrastive Semi-Supervised Learning for Underwater Image Restoration via Reliable Bank,
CVPR23(18145-18155)
IEEE DOI 2309
BibRef

Zhou, J.C.[Jing-Chun], Liu, D.[Dingshuo], Zhang, D.[Dehuan], Zhang, W.S.[Wei-Shi],
Light Attenuation and Color Fluctuation for Underwater Image Restoration,
ACCV22(III:374-389).
Springer DOI 2307
BibRef

Wei, Y.W.[Yi-Wen], Zheng, Z.[Zhuoran], Jia, X.[Xiuyi],
UHD Underwater Image Enhancement via Frequency-spatial Domain Aware Network,
ACCV22(III:21-36).
Springer DOI 2307
BibRef

Tang, Y.[Yi], Iwaguchi, T.[Takafumi], Kawasaki, H.[Hiroshi], Sagawa, R.[Ryusuke], Furukawa, R.[Ryo],
Autoenhancer: Transformer on U-net Architecture Search for Underwater Image Enhancement,
ACCV22(III:120-137).
Springer DOI 2307
BibRef

Desai, C.[Chaitra], Benur, S.[Sujay], Tabib, R.A.[Ramesh Ashok], Patil, U.[Ujwala], Mudenagudi, U.[Uma],
DepthCue: Restoration of Underwater Images Using Monocular Depth as a Clue,
Maritime23(196-205)
IEEE DOI 2302
Degradation, Deep learning, Training, Image color analysis, Absorption, Neural networks, Scattering BibRef

Zhao, W.F.[Wen-Feng], Rong, S.H.[Sheng-Hui], Ma, J.K.[Jian-Kang], He, B.[Bo],
Nonuniform illumination correction for underwater images through a pseudo-siamese network,
ICPR22(1329-1335)
IEEE DOI 2212
Training, Image quality, Imaging, Estimation, Artificial light, Data models, Underwater image enhancement, CABM. BibRef

Li, C.Y.[Chau Yi], Cavallaro, A.[Andrea],
On The Limits of Perceptual Quality Measures for Enhanced Underwater Images,
ICIP22(4148-4152)
IEEE DOI 2211
Image quality, Degradation, Image color analysis, Atmospheric measurements, Volume measurement, colour accuracy BibRef

Huang, M.X.[Meng-Xiao], Wang, Y.[Yang], Zou, W.Q.[Wei-Qi], Cao, Y.[Yang],
Fast Adaptive Self-Supervised Underwater Image Enhancement,
ICIP22(3371-3375)
IEEE DOI 2211
Training, Degradation, Adaptation models, Image color analysis, Absorption, Scattering, Channel estimation, self-supervised BibRef

Fu, Z.Q.[Zhen-Qi], Wang, W.[Wu], Huang, Y.[Yue], Ding, X.H.[Xing-Hao], Ma, K.K.[Kai-Kuang],
Uncertainty Inspired Underwater Image Enhancement,
ECCV22(XVIII:465-482).
Springer DOI 2211
BibRef

Zhai, L.[Lujun], Wang, Y.H.[Yong-Hui], Cui, S.[Suxia], Zhou, Y.[Yu],
Enhancing Underwater Image Using Degradation Adaptive Adversarial Network,
ICIP22(4093-4097)
IEEE DOI 2211
Degradation, Training, Learning systems, Visualization, Adaptation models, Adaptive systems, Image color analysis, unpaired data BibRef

Hodne, L.M.[Lars Martin], Leikvoll, E.[Eirik], Yip, M.[Mauhing], Teigen, A.L.[Andreas Langeland], Stahl, A.[Annette], Mester, R.[Rudolf],
Detecting and Suppressing Marine Snow for Underwater Visual SLAM,
IMW22(5097-5105)
IEEE DOI 2210
Training, Visualization, Simultaneous localization and mapping, Snow, Roads, Pipelines BibRef

Ye, T.[Tian], Chen, S.X.[Si-Xiang], Liu, Y.[Yun], Ye, Y.[Yi], Chen, E.[Erkang], Li, Y.[Yuche],
Underwater Light Field Retention: Neural Rendering for Underwater Imaging,
NTIRE22(487-496)
IEEE DOI 2210
Measurement, Image synthesis, Neural networks, Water quality, Rendering (computer graphics), Visual effects BibRef

Desai, C.[Chaitra], Reddy, B.S.S.[Badduri Sai Sudheer], Tabib, R.A.[Ramesh Ashok], Patil, U.[Ujwala], Mudenagudi, U.[Uma],
AquaGAN: Restoration of Underwater Images,
PBVS22(295-303)
IEEE DOI 2210
Measurement, Training, Learning systems, Image color analysis, Computational modeling, Benchmark testing, Attenuation BibRef

Boudiaf, A.[Abderrahmene], Guo, Y.H.[Yu-Hang], Ghimire, A.[Adarsh], Werghi, N.[Naoufel], de Masi, G.[Giulia], Javed, S.[Sajid], Dias, J.[Jorge],
Underwater Image Enhancement Using Pre-trained Transformer,
CIAP22(III:480-488).
Springer DOI 2205
BibRef

Thapa, S.[Simron], Li, N.Z.[Nian-Zyi], Ye, J.[Jinwei],
Learning to Remove Refractive Distortions from Underwater Images,
ICCV21(4987-4996)
IEEE DOI 2203
Training, Image analysis, Fluctuations, Distortion, Generative adversarial networks, Prediction algorithms, Computational photography BibRef

Menna, F., Nocerino, E., Chemisky, B., Remondino, F., Drap, P.,
Accurate Scaling and Levelling in Underwater Photogrammetry with A Pressure Sensor,
ISPRS21(B2-2021: 667-672).
DOI Link 2201
BibRef

Huo, F.S.[Fu-Shuo], Li, B.H.[Bing-Heng], Zhu, X.G.[Xue-Gui],
Efficient Wavelet Boost Learning-Based Multi-stage Progressive Refinement Network for Underwater Image Enhancement,
AIM21(1944-1952)
IEEE DOI 2112
Degradation, Wavelet transforms, Wavelet domain, Image color analysis, Frequency-domain analysis BibRef

Nakath, D.[David], She, M.[Mengkun], Song, Y.F.[Yi-Fan], Köser, K.[Kevin],
In-Situ Joint Light and Medium Estimation for Underwater Color Restoration,
OceanVision21(3724-3733)
IEEE DOI 2112
Sea surface, Parameter estimation, Image color analysis, Endoscopes, Estimation, Scattering, Ray tracing BibRef

Desai, C.[Chaitra], Tabib, R.A.[Ramesh Ashok], Reddy, S.S.[Sai Sudheer], Patil, U.[Ujwala], Mudenagudi, U.[Uma],
RUIG: Realistic Underwater Image Generation Towards Restoration,
WiCV21(2181-2189)
IEEE DOI 2109
Image synthesis, Wavelength measurement, Current measurement, Scattering, Attenuation BibRef

Li, L.[Lei], Komuro, T.[Takashi], Enomoto, K.[Koichiro], Toda, M.[Masashi],
Removal of Floating Particles from Underwater Images Using Image Transformation Networks,
CVAUI20(414-421).
Springer DOI 2103
BibRef

Song, Y.F.[Yi-Fan], Nakath, D.[David], She, M.[Mengkun], Elibol, F.[Furkan], Köser, K.[Kevin],
Deep Sea Robotic Imaging Simulator,
CVAUI20(375-389).
Springer DOI 2103
BibRef

Song, Y.F.[Yi-Fan], Sticklus, J.[Jan], Nakath, D.[David], Wenzlaff, E.[Emanuel], Koch, R.[Reinhard], Köser, K.[Kevin],
Optimization of Multi-led Setups for Underwater Robotic Vision Systems,
CVAUI20(390-397).
Springer DOI 2103
BibRef

Wang, J.T.[Jiang-Tao], Li, B.H.[Bai-Hua], Zhou, Y.[Yang], Rocco, E.[Emanuele], Meng, Q.G.[Qing-Gang],
Compact and Fast Underwater Segmentation Network for Autonomous Underwater Vehicles,
ACCV20(III:688-703).
Springer DOI 2103
BibRef

She, M., Köser, K.,
Considering Spherical Refraction in Visual Ocean Gas Release Quantification,
CVIDL20(64-69)
IEEE DOI 2102
bubbles, calibration, cameras, flow visualisation, image matching, light refraction, Underwater Camera Calibration BibRef

Ishihara, S., Asano, Y., Zheng, Y., Sato, I.,
Underwater Scene Recovery Using Wavelength-Dependent Refraction of Light,
3DV20(32-40)
IEEE DOI 2102
Surface reconstruction, Surface waves, Cameras, Image reconstruction, Shape, refraction BibRef

Calantropio, A., Chiabrando, F., Seymour, B., Kovacs, E., Lo, E., Rissolo, D.,
Image Pre-processing Strategies for Enhancing Photogrammetric 3d Reconstruction of Underwater Shipwreck Datasets,
ISPRS20(B2:941-948).
DOI Link 2012
BibRef

Ballarin, M., Costa, E., Piemonte, A., Piras, M., Losè, L.T.[L. Teppati],
Underwater Photogrammetry: Potentialities and Problems Results of The Benchmark Session of the 2019 Sifet Congress,
ISPRS20(B2:925-931).
DOI Link 2012
BibRef

Shen, L., Zhao, Y.,
Underwater Image Enhancement Based on Polarization Imaging,
ISPRS20(B1:579-585).
DOI Link 2012
BibRef

Menna, F., Nocerino, E., Ural, S., Gruen, A.,
Mitigating Image Residuals Systematic Patterns In Underwater Photogrammetry,
ISPRS20(B2:977-984).
DOI Link 2012
BibRef

Nocerino, E., Menna, F., Chemisky, B., Drap, P.,
3d Sequential Image Mosaicing for Underwater Navigation and Mapping,
ISPRS20(B2:991-998).
DOI Link 2012
BibRef

Rofallski, R., Tholen, C., Helmholz, P., Parnum, I., Luhmann, T.,
Measuring Artificial Reefs Using A Multi-camera System for Unmanned Underwater Vehicles,
ISPRS20(B2:999-1008).
DOI Link 2012
BibRef

Xiong, J., Zhuang, P., Zhang, Y.,
An Efficient Underwater Image Enhancement Model With Extensive Beer-Lambert Law,
ICIP20(893-897)
IEEE DOI 2011
Image color analysis, Cameras, Mathematical model, Image enhancement, Adaptation models, Image restoration, nonlinear adaptive weight BibRef

Taipalmaa, J., Passalis, N., Raitoharju, J.,
Different Color Spaces In Deep Learning-Based Water Segmentation For Autonomous Marine Operations,
ICIP20(3169-3173)
IEEE DOI 2011
Image color analysis, Training, Image segmentation, Cameras, Robustness, Testing, Unmanned aerial vehicles, Water Segmentation, Autonomous Navigation BibRef

Liu, Y., Rong, S., Cao, X., Li, T., He, B.,
Underwater Image Dehazing Using The Color Space Dimensionality Reduction Prior,
ICIP20(1013-1017)
IEEE DOI 2011
Image color analysis, Estimation, Dimensionality reduction, Image restoration, Indexes, Optical imaging, Adaptive optics, transmission estimation BibRef

Li, C.Y., Cavallaro, A.,
Cast-GAN: Learning To Remove Colour Cast From Underwater Images,
ICIP20(1083-1087)
IEEE DOI 2011
Image color analysis, Attenuation, Training, Image enhancement, Scattering, Neural networks, Cameras, Image enhancement, Image synthesis BibRef

Marques, T.P., Albu, A.B.[A. Branzan],
L2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion,
NTIRE20(2286-2295)
IEEE DOI 2008
Lighting, Image color analysis, Atmospheric modeling, Mathematical model, Visualization, Biological system modeling, Cameras BibRef

James, J.G., Rajwade, A.,
Fourier Based Pre-Processing For Seeing Through Water,
WACV20(109-117)
IEEE DOI 2006
Optical surface waves, Surface waves, Distortion, Tracking, Cameras, Trajectory, Strain BibRef

James, J.G., Agrawal, P., Rajwade, A.,
Restoration of Non-Rigidly Distorted Underwater Images Using a Combination of Compressive Sensing and Local Polynomial Image Representations,
ICCV19(7838-7847)
IEEE DOI 2004
compressed sensing, discrete Fourier transforms, feature extraction, image representation, image restoration, Optical imaging BibRef

Ueda, T., Yamada, K., Tanaka, Y.,
Underwater Image Synthesis from RGB-D Images and its Application to Deep Underwater Image Restoration,
ICIP19(2115-2119)
IEEE DOI 1910
Underwater image restoration, deep neural network, underwater image synthesis BibRef

Ichimaru, K., Kawasaki, H.,
Underwater Stereo Using Refraction-Free Image Synthesized From Light Field Camera,
ICIP19(1039-1043)
IEEE DOI 1910
Stereo vision, Refraction, Light field, Underwater shape reconstruction BibRef

Neyer, F., Nocerino, E., Gruen, A.,
Image Quality Improvements in Low-cost Underwater Photogrammetry,
Underwater19(135-142).
DOI Link 1904
BibRef

Protasiuk, R., Bibi, A., Ghanem, B.,
Local Color Mapping Combined with Color Transfer for Underwater Image Enhancement,
WACV19(1433-1439)
IEEE DOI 1904
affine transforms, covariance analysis, image colour analysis, image enhancement, local color mapping, affine transform model, Lighting BibRef

Marques, T.P.[Tunai Porto], Albu, A.B.[Alexandra Branzan], Hoeberechts, M.[Maia],
Enhancement of Low-Lighting Underwater Images Using Dark Channel Prior and Fast Guided Filters,
CVAUI18(55-65).
Springer DOI 1901
BibRef

Yu, X.L.[Xiao-Li], Qu, Y.Y.[Yan-Yun], Hong, M.[Ming],
Underwater-GAN: Underwater Image Restoration via Conditional Generative Adversarial Network,
CVAUI18(66-75).
Springer DOI 1901
BibRef

Li, C.Y.[Chau Yi], Mazzon, R.[Riccardo], Cavallaro, A.[Andrea],
An Online Platform for Underwater Image Quality Evaluation,
CVAUI18(37-44).
Springer DOI 1901
BibRef

Cao, K., Peng, Y., Cosman, P.C.,
Underwater Image Restoration using Deep Networks to Estimate Background Light and Scene Depth,
Southwest18(1-4)
IEEE DOI 1809
Image restoration, Estimation, Training, Network architecture, Image color analysis, Cameras, Attenuation, Underwater images, convolutional neural networks BibRef

Varghese, V., Bryson, M., Pizarro, O., Williams, S.B., Dansereau, D.G.,
Light Field Image Restoration for Vision in Scattering Media,
ICIP18(1093-1097)
IEEE DOI 1809
Image restoration, Backscatter, Scattering, Image color analysis, Media, Imaging, Pipelines, Image restoration, image enhancement, underwater imaging BibRef

Li, C.Y., Cavallaro, A.,
Background Light Estimation for Depth-Dependent Underwater Image Restoration,
ICIP18(1528-1532)
IEEE DOI 1809
Image color analysis, Image restoration, Attenuation, Cameras, Channel estimation, Estimation, Scattering, Spectral distortion, colour correction BibRef

Gautam, S., Gandhi, T.K., Panigrahi, B.K.,
An Advanced Visibility Restoration Technique for Underwater Images,
ICIP18(1757-1761)
IEEE DOI 1809
Image restoration, Image color analysis, Atmospheric modeling, Estimation, Channel estimation, Scattering, Imaging, visibility enhancement BibRef

Barbosa, W.V., Amaral, H.G.B., Rocha, T.L., Nascimento, E.R.,
Visual-Quality-Driven Learning for Underwater Vision Enhancement,
ICIP18(3933-3937)
IEEE DOI 1809
Image restoration, Measurement, Training, Visualization, Image quality, Cameras, Media, Underwater Vision, Image Restoration, Deep Learning BibRef

Yang, J., Wang, X., Yue, H., Fu, X., Hou, C.,
Underwater image enhancement based on structure-texture decomposition,
ICIP17(1207-1211)
IEEE DOI 1803
Absorption, Colored noise, Estimation, Image color analysis, Image enhancement, Image restoration, Reliability, structure-texture decomposition BibRef

Baba, T., Nakamura, K., Kyochi, S., Okuda, M.,
Image enhancement method for underwater images based on discrete cosine eigenbasis transformation,
ICIP17(4272-4276)
IEEE DOI 1803
Correlation, Covariance matrices, Discrete cosine transforms, Eigenvalues and eigenfunctions, Image color analysis, Underwater images BibRef

Chadebecq, F.[François], Vasconcelos, F.[Francisco], Dwyer, G.[George], Lacher, R.[Reé], Ourselin, S.[Sébastien], Vercauteren, T.[Tom], Stoyanov, D.[Danail],
Refractive Structure-from-Motion Through a Flat Refractive Interface,
ICCV17(5325-5333)
IEEE DOI 1802
Underwater images. cameras, geometry, geophysical image processing, image motion analysis, image sensors, light propagation, BibRef

Palmér, T.[Tobias], Åström, K.[Kalle], Frahm, J.M.[Jan-Michael],
The Misty Three Point Algorithm for Relative Pose,
CVPR17(4551-4559)
IEEE DOI 1711
Applied to underwater images. Attenuation, Cameras, Estimation, Geometry, Image color analysis, Mathematical, model BibRef

Skinner, K.A., Johnson-Roberson, M.,
Underwater Image Dehazing with a Light Field Camera,
LightField17(1775-1782)
IEEE DOI 1709
Atmospheric modeling, Attenuation, Backscatter, Cameras, Lighting, Storage, tanks BibRef

Ponce-Hinestroza, A.N., Torres-Méndez, L.A., Drews, P.,
Using a MRF-BP model with color adaptive training for underwater color restoration,
ICPR16(787-792)
IEEE DOI 1705
Adaptation models, Image color analysis, Image restoration, Markov random fields, Robots, Training, Video, sequences BibRef

Digumarti, S.T., Chaurasia, G., Taneja, A., Siegwart, R., Thomas, A., Beardsley, P.,
Underwater 3D capture using a low-cost commercial depth camera,
WACV16(1-9)
IEEE DOI 1511
Atmospheric modeling BibRef

Emberton, S.[Simon], Chittka, L.[Lars], Cavallaro, A.[Andrea],
Hierarchical rank-based veiling light estimation for underwater dehazing,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Fu, X.Y.[Xue-Yang], Zhuang, P.X.[Pei-Xian], Huang, Y.[Yue], Liao, Y.H.[Ying-Hao], Zhang, X.P.[Xiao-Ping], Ding, X.H.[Xing-Hao],
A retinex-based enhancing approach for single underwater image,
ICIP14(4572-4576)
IEEE DOI 1502
Green products BibRef

Maas, H.G.[Hans-Gerd],
A Modular Geometric Model for Underwater Photogrammetry,
Underwater15(139-141).
DOI Link 1508
BibRef

Mulsow, C.[Christian], Maas, H.G.[Hans-Gerd],
A Universal Approach for Geometric Modelling in Underwater Stereo Image Processing,
CVAUI14(49-56)
IEEE DOI 1402
Cameras BibRef

Drap, P., Merad, D., Mahiddine, A., Seinturier, J., Gerenton, P., Peloso, D., Boï, P.M., Bianchimani, O., Garrabou, J.,
Automating the Measurement of Red Coral in Situ Using Underwater Photogrammetry and Coded Targets,
CIPA13(231-236).
DOI Link 1311
BibRef

Schechner, Y.Y., Diner, D.J., Martonchik, J.V.,
Spaceborne underwater imaging,
ICCP11(1-8).
IEEE DOI 1208
BibRef

Barngrover, C.[Christopher], Belongie, S.J.[Serge J.], Kastner, R.[Ryan],
JBoost Optimization of Color Detectors for Autonomous Underwater Vehicle Navigation,
CAIP11(II: 155-162).
Springer DOI 1109
BibRef

Åhlén, J., Sundgren, D., Lindell, T., Bengtsson, E.,
Dissolved Organic Matters Impact on Colour Reconstruction in Underwater Images,
SCIA05(1148-1156).
Springer DOI 0506
BibRef

Stewart, W.K.,
Remote-sensing issues for intelligent underwater systems,
CVPR91(230-235).
IEEE DOI 0403
BibRef

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Underwater Images, Color Correction .