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.,
Losč, 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],
Ĺström, 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.,
Boď, 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
Ĺhlén, 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 .