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
Zotta, L.,
Matteoli, S.,
Diani, M.,
Corsini, G.,
AFRODiTE: A FluoRescence Lidar Simulator for Underwater Object
DeTEction Applications,
GeoRS(53), No. 6, June 2015, pp. 3022-3041.
IEEE DOI
1503
oceanographic regions
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
Lu, H.M.[Hui-Min],
Li, Y.J.[Yu-Jie],
Zhang, L.F.[Li-Feng],
Serikawa, S.[Seiichi],
Contrast enhancement for images in turbid water,
JOSA-A(32), No. 5, May 2015, pp. 886-893.
DOI Link
1505
BibRef
Earlier: A1, A2, A4, Only:
Underwater image enhancement using guided trigonometric bilateral
filter and fast automatic color correction,
ICIP13(3412-3416)
IEEE DOI
1402
Image enhancement, Imaging through turbid media.
Underwater imaging, bilateral filter, color correction, image enhancement
BibRef
Lu, H.M.[Hui-Min],
Li, Y.J.[Yu-Jie],
Xu, X.[Xing],
Li, J.R.[Jian-Ru],
Liu, Z.F.[Zhi-Fei],
Li, X.[Xin],
Yang, J.M.[Jian-Min],
Serikawa, S.[Seiichi],
Underwater image enhancement method using weighted guided
trigonometric filtering and artificial light correction,
JVCIR(38), No. 1, 2016, pp. 504-516.
Elsevier DOI
1605
Deep-sea imaging
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
Li, C.,
Guo, J.,
Guo, C.,
Emerging From Water: Underwater Image Color Correction Based on
Weakly Supervised Color Transfer,
SPLetters(25), No. 3, March 2018, pp. 323-327.
IEEE DOI
1802
Atmospheric modeling, Image color analysis, Loss measurement,
Scattering, Training, Visualization, Color casts,
underwater image
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
Nomura, K.,
Sugimura, D.,
Hamamoto, T.,
Underwater Image Color Correction using Exposure-Bracketing Imaging,
SPLetters(25), No. 6, June 2018, pp. 893-897.
IEEE DOI
1806
BibRef
Earlier:
Color correction of underwater images based on multi-illuminant
estimation with exposure bracketing imaging,
ICIP17(705-709)
IEEE DOI
1803
geophysical image processing, image colour analysis,
image fusion, oceanographic techniques, regression analysis,
underwater image.
Attenuation, Distortion, Estimation,
Imaging, Optical distortion, Color correction,
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.[Lipeng],
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
Gao, S.,
Zhang, M.,
Zhao, Q.,
Zhang, X.,
Li, Y.,
Underwater Image Enhancement Using Adaptive Retinal Mechanisms,
IP(28), No. 11, November 2019, pp. 5580-5595.
IEEE DOI
1909
Image color analysis, Retina, Radio frequency, Ganglia,
Photoreceptors, Adaptation models, Image edge detection,
color correction
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, Pattern recognition, 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
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
Kannan, S.[Srividhya],
Intelligent object recognition in underwater images using
evolutionary-based Gaussian mixture model and shape matching,
SIViP(14), No. 5, July 2020, pp. 877-885.
Springer DOI
2006
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
Szymak, P.[Piotr],
Piskur, P.[Pawel],
Naus, K.[Krzysztof],
The Effectiveness of Using a Pretrained Deep Learning Neural Networks
for Object Classification in Underwater Video,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Ye, X.,
Li, Z.,
Sun, B.,
Wang, Z.,
Xu, R.,
Li, H.,
Fan, X.,
Deep Joint Depth Estimation and Color Correction From Monocular
Underwater Images Based on Unsupervised Adaptation Networks,
CirSysVideo(30), No. 11, November 2020, pp. 3995-4008.
IEEE DOI
2011
Image color analysis, Estimation, Task analysis, Color,
Visualization, Robots, Atmospheric modeling, Underwater image,
domain adapatation
BibRef
Zhang, W.D.[Wei-Dong],
Dong, L.L.[Li-Li],
Zhang, T.[Tong],
Xu, W.H.[Wen-Hai],
Enhancing underwater image via color correction and Bi-interval
contrast enhancement,
SP:IC(90), 2021, pp. 116030.
Elsevier DOI
2012
Underwater image enhancement, Color correctio,
Contrast enhancement, Enhancing details
BibRef
Zhang, W.D.[Wei-Dong],
Zhuang, P.X.[Pei-Xian],
Sun, H.H.[Hai-Han],
Li, G.[Guohou],
Kwong, S.[Sam],
Li, C.Y.[Chong-Yi],
Underwater Image Enhancement via Minimal Color Loss and Locally
Adaptive Contrast Enhancement,
IP(31), 2022, pp. 3997-4010.
IEEE DOI
2206
Image color analysis, Attenuation, Imaging, Channel estimation,
Image enhancement, Degradation, Learning systems,
underwater imaging
BibRef
Dong, L.L.[Li-Li],
Zhang, W.D.[Wei-Dong],
Xu, W.H.[Wen-Hai],
Underwater image enhancement via integrated RGB and LAB color models,
SP:IC(104), 2022, pp. 116684.
Elsevier DOI
2204
Underwater image color shift, Color correction,
Local enhancement, Gain equalization
BibRef
Liu, R.,
Fan, X.,
Zhu, M.,
Hou, M.,
Luo, Z.,
Real-World Underwater Enhancement: Challenges, Benchmarks, and
Solutions Under Natural Light,
CirSysVideo(30), No. 12, December 2020, pp. 4861-4875.
IEEE DOI
2012
Image color analysis, Image enhancement, Task analysis, Histograms,
Benchmark testing, Imaging, Degradation,
object detection
BibRef
Deng, J.J.[Jun-Jie],
Luo, G.[Gege],
Zhao, C.D.[Cai-Dan],
UCT-GAN: underwater image colour transfer generative adversarial
network,
IET-IPR(14), No. 14, December 2020, pp. 3613-3622.
DOI Link
2012
BibRef
Liu, J.,
Zhang, X.,
Parameter-Adaptive Compensation (PAC) for Processing Underwater
Selective Absorption,
SPLetters(27), 2020, pp. 2178-2182.
IEEE DOI
2012
Image color analysis,
Picture archiving and communication systems, Attenuation,
underwater image enhancement
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
Huang, Y.F.[Yi-Fan],
Liu, M.Y.[Man-Yu],
Yuan, F.[Fei],
Color correction and restoration based on multi-scale recursive
network for underwater optical image,
SP:IC(93), 2021, pp. 116174.
Elsevier DOI
2103
Underwater image, Style transfer, Color correction,
Image enhancement, Convolutional neural network
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
Chen, L.[Long],
Jiang, Z.[Zheheng],
Tong, L.[Lei],
Liu, Z.H.[Zhi-Hua],
Zhao, A.[Aite],
Zhang, Q.[Qianni],
Dong, J.Y.[Jun-Yu],
Zhou, H.Y.[Hui-Yu],
Perceptual Underwater Image Enhancement With Deep Learning and
Physical Priors,
CirSysVideo(31), No. 8, August 2021, pp. 3078-3092.
IEEE DOI
2108
Task analysis, Image enhancement, Image color analysis, Absorption,
Image synthesis, Deep learning, Object detection,
perceptual loss
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.[Junkang],
Jiang, Q.P.[Qiu-Ping],
Cong, R.[Runmin],
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
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
Xie, J.[Jun],
Hou, G.J.[Guo-Jia],
Wang, G.D.[Guo-Dong],
Pan, Z.[Zhenkuan],
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
Liang, Z.[Zheng],
Ding, X.Y.[Xue-Yan],
Wang, Y.F.[Ya-Fei],
Yan, X.H.[Xiao-Hong],
Fu, X.P.[Xian-Ping],
GUDCP: Generalization of Underwater Dark Channel Prior for Underwater
Image Restoration,
CirSysVideo(32), No. 7, July 2022, pp. 4879-4884.
IEEE DOI
2207
Image color analysis, Channel estimation, Estimation, Attenuation,
Image restoration, Lighting, Cameras, Underwater image enhancement,
color correction
BibRef
Liu, R.S.[Ri-Sheng],
Jiang, Z.Y.[Zhi-Ying],
Yang, S.Z.[Shu-Zhou],
Fan, X.[Xin],
Twin Adversarial Contrastive Learning for Underwater Image
Enhancement and Beyond,
IP(31), 2022, pp. 4922-4936.
IEEE DOI
2208
Task analysis, Image enhancement, Detectors, Image restoration,
Object detection, Image color analysis, Visualization,
generative adversarial learning
BibRef
Huang, Y.F.[Yi-Fan],
Yuan, F.[Fei],
Xiao, F.Q.[Feng-Qi],
Cheng, E.[En],
Underwater image enhancement based on color restoration and dual
image wavelet fusion,
SP:IC(107), 2022, pp. 116797.
Elsevier DOI
2208
Underwater image, Color compensation, Color restoration,
Image enhancement, Image wavelet fusion, Generative adversarial network
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
Gu, C.J.[Chang-Jun],
Cong, Y.[Yang],
Sun, G.[Gan],
Gao, Y.[Yajun],
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.[Ziwei],
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
Chen, L.[Long],
Zhou, F.[Feixiang],
Wang, S.[Shengke],
Dong, J.Y.[Jun-Yu],
Li, N.[Ning],
Ma, H.P.[Hai-Ping],
Wang, X.[Xin],
Zhou, H.Y.[Hui-Yu],
SWIPENET: Object detection in noisy underwater scenes,
PR(132), 2022, pp. 108926.
Elsevier DOI
2209
Underwater object detection, Curriculum Multi-Class Adaboost,
Sample-weighted detection loss, Noisy data
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
Jia, J.Q.[Jia-Qi],
Fu, M.[Min],
Liu, X.F.[Xue-Feng],
Zheng, B.[Bing],
Underwater Object Detection Based on Improved EfficientDet,
RS(14), No. 18, 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
Jiang, Z.[Zhiying],
Li, Z.X.[Zhuo-Xiao],
Yang, S.[Shuzhou],
Fan, X.[Xin],
Liu, R.[Risheng],
Target Oriented Perceptual Adversarial Fusion Network for Underwater
Image Enhancement,
CirSysVideo(32), No. 10, October 2022, pp. 6584-6598.
IEEE DOI
2210
Image color analysis, Image restoration, Degradation,
Deep learning, Image enhancement, Absorption, Image reconstruction,
color correction
BibRef
Xue, X.W.[Xin-Wei],
Li, Z.X.[Ze-Xuanxo],
Ma, L.[Long],
Jia, Q.[Qi],
Liu, R.[Risheng],
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.[Yufei],
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.[Yaozu],
Jiang, Q.P.[Qiu-Ping],
Li, C.Y.[Chong-Yi],
Ren, W.Q.[Wen-Qi],
Liu, H.T.[Han-Tao],
Wang, P.[Pengjun],
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
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
Muniraj, M.[Manigandan],
Dhandapani, V.[Vaithiyanathan],
Underwater image enhancement by modified color correction and
adaptive Look-Up-Table with edge-preserving filter,
SP:IC(113), 2023, pp. 116939.
Elsevier DOI
2303
Color correction, Underwater image enhancement, CLAHE,
Look-up table histogram manipulation, LAB color space, Image denoise
BibRef
Espinosa, A.R.[Alejandro Rico],
McIntosh, D.[Declan],
Albu, A.B.[Alexandra Branzan],
An Efficient Approach for Underwater Image Improvement:
Deblurring, Dehazing, and Color Correction,
Maritime23(206-215)
IEEE DOI
2302
Training, Degradation, Visualization, Image color analysis,
Real-time systems, Data models, Discrete wavelet transforms
BibRef
Cai, Y.[Ye],
Gao, H.X.[Hong-Xia],
Niu, S.C.[Shi-Cheng],
Qi, T.[Tian],
Yang, W.P.[Wei-Peng],
A multi-stage restoration method for degraded images with light
scattering and absorption,
ICPR22(407-413)
IEEE DOI
2212
Visualization, Image color analysis, Absorption,
Image edge detection, Lighting, Light scattering, Color correction
BibRef
Zhao, W.F.[Wen-Feng],
Rong, S.[Shenghui],
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.[Sixiang],
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
Pipara, A.[Arpit],
Oza, U.[Urvi],
Mandal, S.[Srimanta],
Underwater Image Color Correction Using Ensemble Colorization Network,
AIM21(2011-2020)
IEEE DOI
2112
Measurement, Degradation, Deep learning, Image color analysis,
Surveillance, Visual systems
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
Liu, H.,
Song, P.,
Ding, R.,
Towards Domain Generalization In Underwater Object Detection,
ICIP20(1971-1975)
IEEE DOI
2011
Training, Detectors, Feature extraction, Task analysis,
Object detection, Biological system modeling, Semantics,
domain invariance
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
Fan, B.J.[Bao-Jie],
Chen, W.[Wei],
Cong, Y.[Yang],
Tian, J.D.[Jian-Dong],
Dual Refinement Underwater Object Detection Network,
ECCV20(XX:275-291).
Springer DOI
2011
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
Zhang, W.,
Li, G.,
Ying, Z.,
A new underwater image enhancing method via color correction and
illumination adjustment,
VCIP17(1-4)
IEEE DOI
1804
image colour analysis, image enhancement, color cast,
color correction, color enhancement method, gamma correction,
visual performance
BibRef
Ancuti, C.O.,
Ancuti, C.,
de Vleeschouwer, C.,
Neumann, L.,
Garcia, R.,
Color transfer for underwater dehazing and depth estimation,
ICIP17(695-699)
IEEE DOI
1803
Attenuation, Colored noise, Estimation, Image color analysis,
Image edge detection, Image restoration, Imaging, color constancy,
underwater visibility enhancement
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
Wang, Y.,
Zhang, J.[Jing],
Cao, Y.[Yang],
Wang, Z.F.[Zeng-Fu],
A deep CNN method for underwater image enhancement,
ICIP17(1382-1386)
IEEE DOI
1803
Attenuation, Distortion, Feature extraction, Image color analysis,
Image enhancement, Imaging, Training, color correction, deep CNN,
underwater image enhancement
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).
HTML Version.
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
Torres-Méndez, L.A.[Luz A.],
Dudek, G.[Gregory],
Color Correction of Underwater Images for Aquatic Robot Inspection,
EMMCVPR05(60-73).
Springer DOI
0601
BibRef
Ĺhlen, J.[Julia],
Sundgren, D.[David],
Bottom Reflectance Influence on a Color Correction Algorithm for
Underwater Images,
SCIA03(922-926).
Springer DOI
0310
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
Color Sensors, Sensor Models .