经典和先进的水下图像去雾方法综述

周景春; 张得欢; 张维石

doi:10.1631/FITEE.2000190

Your Location：

Home >

Browse articles >

经典和先进的水下图像去雾方法综述

常规文章 | Updated：2022-05-19

- 经典和先进的水下图像去雾方法综述
  Enhanced Publication
- Classical and state-of-the-art approaches for underwater image defogging: a comprehensive survey
- 信息与电子工程前沿（英文） 2020年21卷第12期页码：1745-1769
- Affiliations：
  
  College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
- Author bio：
  
  [ "Jing-chun ZHOU, E-mail: zhoujingchun@dlmu.edu.cn" ]
  [ "De-huan ZHANG, E-mail: zhangdehuan@dlmu.edu.cn" ]
  Wei-shi ZHANG, E-mail: teesiv@dlmu.edu.cn
- Funds：
  
  Project supported by the National Natural Science Foundation of China (No. 61702074), the Liaoning Provincial Natural Science Foundation of China (No. 20170520196), and the Fundamental Research Funds for the Central Universities, China (Nos. 3132019205 and 3132019354)
- DOI：10.1631/FITEE.2000190
  中图分类号： TP391.4
- 纸质出版日期：2020-12，
  
  收稿日期：2020-04-23，
  
  修回日期：2020-11-11，
- Accepted：
Scan QR Code
周景春, 张得欢, 张维石. 经典和先进的水下图像去雾方法综述[J]. 信息与电子工程前沿（英文）, 2020,21(12):1745-1769.

JING-CHUN ZHOU, DE-HUAN ZHANG, WEI-SHI ZHANG. Classical and state-of-the-art approaches for underwater image defogging: a comprehensive survey. [J]. Frontiers of information technology & electronic engineering, 2020, 21(12): 1745-1769.
周景春, 张得欢, 张维石. 经典和先进的水下图像去雾方法综述[J]. 信息与电子工程前沿（英文）, 2020,21(12):1745-1769. DOI： 10.1631/FITEE.2000190.

JING-CHUN ZHOU, DE-HUAN ZHANG, WEI-SHI ZHANG. Classical and state-of-the-art approaches for underwater image defogging: a comprehensive survey. [J]. Frontiers of information technology & electronic engineering, 2020, 21(12): 1745-1769. DOI： 10.1631/FITEE.2000190.

摘要

在水下场景中，成像系统获取的视频和图像质量严重下降，影响目标的检测和识别。因此，从模糊的视频和图像中恢复真实场景具有重要意义。由于悬浮粒子对光线的吸收和散射作用，获取的图像往往能见度低，存在偏色、对比度低、噪声和模糊等问题。本文旨在对水下图像去雾的重要技术进行分类和比较，为本领域研究人员分析当前研究现状。通过广泛的文献调研，首先分析水下图像退化原因和水下光学成像模型。将现有水下图像去雾方法分为3类，包括水下图像复原方法、水下图像增强方法和基于深度学习的去雾方法。然后，总结水下图像客观质量评价方法，并对经典和当前流行的水下图像去雾方法的性能进行比较分析。最后指出当前水下图像复原和增强技术存在的不足，展望未来的7个研究方向。

Abstract

In underwater scenes

the quality of the video and image acquired by the underwater imaging system suffers from severe degradation

influencing target detection and recognition. Thus

restoring real scenes from blurred videos and images is of great significance. Owing to the light absorption and scattering by suspended particles

the images acquired often have poor visibility

including color shift

low contrast

noise

and blurring issues. This paper aims to classify and compare some of the significant technologies in underwater image defogging

presenting a comprehensive picture of the current research landscape for researchers. First we analyze the reasons for degradation of underwater images and the underwater optical imaging model. Then we classify the underwater image defogging technologies into three categories

including image restoration approaches

image enhancement approaches

and deep learning approaches. Afterward

we present the objective evaluation metrics and analyze the state-of-the-art approaches. Finally

we summarize the shortcomings of the defogging approaches for underwater images and propose seven research directions.

关键词

水下图像去雾复原方法增强方法评价指标

Keywords

Underwater image defoggingRestoration approachesEnhancement approachesEvaluation metrics

references

A Abu, , , R Diamant. . Unsupervised local spatial mixture segmentation of underwater objects in sonar images. . IEEE J Ocean Eng, , 2019. . 44((4):):1179--1197. . DOI:10.1109/JOE.2018.2863961http://doi.org/10.1109/JOE.2018.2863961..

RSM Alex, , , MH Supriya. . Underwater image enhancement using single scale retinex on a reconfigurable hardware. . Int Symp on Ocean Electronics, , 2015. . p.1--5. . DOI:10.1109/SYMPOL.2015.7581166http://doi.org/10.1109/SYMPOL.2015.7581166..

KO Amer, , , M Elbouz, , , A Alfalou. . Enhancing underwater optical imaging by using a low-pass polarization filter. . Opt Expr, , 2019. . 27((2):):621--643. . DOI:10.1364/OE.27.000621http://doi.org/10.1364/OE.27.000621..

C Ancuti, , , CO Ancuti, , , T Haber, , , 等. . Enhancing underwater images and videos by fusion. . IEEE Conf on Computer Vision and Pattern Recognition, , 2012. . p.81--88. . DOI:10.1109/CVPR.2012.6247661http://doi.org/10.1109/CVPR.2012.6247661..

CO Ancuti, , , C Ancuti, , , C de Vleeschouwer, , , 等. . Color balance and fusion for underwater image enhancement. . IEEE Trans Image Process, , 2018. . 27((1):):379--393. . DOI:10.1109/TIP.2017.2759252http://doi.org/10.1109/TIP.2017.2759252..

S Anwar, , , CY Li. . Diving deeper into underwater image enhancement: a survey. . Signal Process Image Commun, , 2020. . 89115978DOI:10.1016/j.image.2020.115978http://doi.org/10.1016/j.image.2020.115978..

KZM Azmi, , , ASA Ghani, , , ZM Yusof, , , 等. . Natural-based underwater image color enhancement through fusion of swarm-intelligence algorithm. . Appl Soft Comput, , 2019. . 85105810DOI:10.1016/j.asoc.2019.105810http://doi.org/10.1016/j.asoc.2019.105810..

L Bai, , , W Zhang, , , X Pan, , , 等. . Underwater image enhancement based on global and local equalization of histogram and dual-image multi-scale fusion. . IEEE Access, , 2020. . 8128973--128990. . DOI:10.1109/ACCESS.2020.3009161http://doi.org/10.1109/ACCESS.2020.3009161..

G Buchsbaum. . A spatial processor model for object colour perception. . J Franklin Inst, , 1980. . 310((1):):1--26. . DOI:10.1016/0016-0032(80)90058-7http://doi.org/10.1016/0016-0032(80)90058-7..

BL Cai, , , XM Xu, , , K Jia, , , 等. . DehazeNet: an end-to-end system for single image haze removal. . IEEE Trans Image Process, , 2016. . 25((11):):5187--5198. . DOI:10.1109/TIP.2016.2598681http://doi.org/10.1109/TIP.2016.2598681..

WW Cai, , , ZG Wei. . PiiGAN: generative adversarial networks for pluralistic image inpainting. . IEEE Access, , 2020. . 848451--48463. . DOI:10.1109/ACCESS.2020.2979348http://doi.org/10.1109/ACCESS.2020.2979348..

N Carlevaris-Bianco, , , A Mohan, , , RM Eustice. . Initial results in underwater single image dehazing. . OCEANS 2010 MTS/IEEE SEATTLE, , 2010. . p.1--8. . DOI:10.1109/OCEANS.2010.5664428http://doi.org/10.1109/OCEANS.2010.5664428..

YK Chang, , , CL Jung, , , P Ke, , , 等. . Automatic contrast-limited adaptive histogram equalization with dual Gamma correction. . IEEE Access, , 2018. . 611782--11792. . DOI:10.1109/ACCESS.2018.2797872http://doi.org/10.1109/ACCESS.2018.2797872..

L Chao, , , M Wang. . Removal of water scattering. . Proc 2nd Int Conf on Computer Engineering and Technology, , 2010. . p.35--39. . DOI:10.1109/ICCET.2010.5485339http://doi.org/10.1109/ICCET.2010.5485339..

XY Chen, , , JZ Yu, , , SH Kong, , , 等. . Towards real-time advancement of underwater visual quality with GAN. . IEEE Trans Ind Electron, , 2019. . 66((12):):9350--9359. . DOI:10.1109/TIE.2019.2893840http://doi.org/10.1109/TIE.2019.2893840..

JY Chiang, , , YC Chen. . Underwater image enhancement by wavelength compensation and dehazing. . IEEE Trans Image Process, , 2012. . 21((4):):1756--1769. . DOI:10.1109/TIP.2011.2179666http://doi.org/10.1109/TIP.2011.2179666..

CG Dai, , , MX Lin, , , XJ Wu, , , 等. . Single underwater image restoration by decomposing curves of attenuating color. . Opt Laser Technol, , 2020. . 123105947DOI:10.1016/j.optlastec.2019.105947http://doi.org/10.1016/j.optlastec.2019.105947..

H Demirel, , , G Anbarjafari. . IMAGE resolution enhancement by using discrete and stationary wavelet decomposition. . IEEE Trans Image Process, , 2011. . 20((5):):1458--1460. . DOI:10.1109/TIP.2010.2087767http://doi.org/10.1109/TIP.2010.2087767..

G Deng. . A generalized unsharp masking algorithm. . IEEE Trans Image Process, , 2011. . 20((5):):1249--1261. . DOI:10.1109/TIP.2010.2092441http://doi.org/10.1109/TIP.2010.2092441..

XY Deng, , , HG Wang, , , X Liu. . Underwater image enhancement based on removing light source color and dehazing. . IEEE Access, , 2019. . 7114297--114309. . DOI:10.1109/ACCESS.2019.2936029http://doi.org/10.1109/ACCESS.2019.2936029..

XY Ding, , , YF Wang, , , J Zhang, , , 等. . Underwater image dehaze using scene depth estimation with adaptive color correction. . OCEANS Aberdeen, , 2017. . p.1--5. . DOI:10.1109/OCEANSE.2017.8084665http://doi.org/10.1109/OCEANSE.2017.8084665..

PJr Drews, , , Nascimento E Do, , , F Moraes, , , 等. . Transmission estimation in underwater single images. . Proc IEEE Int Conf on Computer Vision Workshops, , 2013. . p.825--830. . DOI:10.1109/ICCVW.2013.113http://doi.org/10.1109/ICCVW.2013.113..

SQ Duntley. . Light in the sea. . J Opt Soc Am, , 1963. . 53((2):):214--233. . DOI:10.1364/JOSA.53.000214http://doi.org/10.1364/JOSA.53.000214..

C Fabbri, , , MJ Islam, , , J Sattar. . Enhancing underwater imagery using generative adversarial networks. . IEEE Int Conf on Robotics and Automation, , 2018. . p.7159--7165. . DOI:10.1109/ICRA.2018.8460552http://doi.org/10.1109/ICRA.2018.8460552..

GD Finlayson, , , E Trezzi. . Shades of gray and colour constancy. . Proc 12th Color Imaging Conf, , 2004. . p.37--41. . ..

XY Fu, , , PX Zhuang, , , Y Huang, , , 等. . A retinex-based enhancing approach for single underwater image. . IEEE Int Conf on Image Processing, , 2014. . p.4572--4576. . DOI:10.1109/ICIP.2014.7025927http://doi.org/10.1109/ICIP.2014.7025927..

XY Fu, , , YH Liao, , , DL Zeng, , , 等. . A probabilistic method for image enhancement with simultaneous illumination and reflectance estimation. . IEEE Trans Image Process, , 2015. . 24((12):):4965--4977. . DOI:10.1109/TIP.2015.2474701http://doi.org/10.1109/TIP.2015.2474701..

A Galdran, , , D Pardo, , , A Picón, , , 等. . Automatic red-channel underwater image restoration. . J Vis Commun Image Represent, , 2015. . 26132--145. . DOI:10.1016/j.jvcir.2014.11.006http://doi.org/10.1016/j.jvcir.2014.11.006..

SB Gao, , , M Zhang, , , Q Zhao, , , 等. . Underwater image enhancement using adaptive retinal mechanisms. . IEEE Trans Image Process, , 2019. . 28((11):):5580--5595. . DOI:10.1109/TIP.2019.2919947http://doi.org/10.1109/TIP.2019.2919947..

ASA Ghani, , , NAM Isa. . Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching. . SpringerPlus, , 2014. . 3((1):):757DOI:10.1186/2193-1801-3-757http://doi.org/10.1186/2193-1801-3-757..

ASA Ghani, , , NAM Isa. . Underwater image quality enhancement through integrated color model with Rayleigh distribution. . Appl Soft Comput, , 2015a. . 27219--230. . DOI:10.1016/j.asoc.2014.11.020http://doi.org/10.1016/j.asoc.2014.11.020..

ASA Ghani, , , NAM Isa. . Enhancement of low quality underwater image through integrated global and local contrast correction. . Appl Soft Comput, , 2015b. . 37332--344. . DOI:10.1016/j.asoc.2015.08.033http://doi.org/10.1016/j.asoc.2015.08.033..

ASA Ghani, , , NAM Isa. . Automatic system for improving underwater image contrast and color through recursive adaptive histogram modification. . Comput Electron Agric, , 2017. . 141181--195. . DOI:10.1016/j.compag.2017.07.021http://doi.org/10.1016/j.compag.2017.07.021..

ASA Ghani, , , RSNAR Aris, , , MLM Zain. . Unsupervised contrast correction for underwater image quality enhancement through integrated-intensity stretched-Rayleigh histograms. . J Telecomm Electron Comput Eng, , 2016. . 8((3):):1--7. . ..

GC Giakos. . Active backscattered optical polarimetric imaging of scattered targets. . Proc 21st IEEE Instrumentation and Measurement Technology Conf, , 2004. . p.430--432. . DOI:10.1109/IMTC.2004.1351080http://doi.org/10.1109/IMTC.2004.1351080..

A Gijsenij, , , T Gevers, , , J van de Weijer. . Improving color constancy by photometric edge weighting. . IEEE Trans Patt Anal Mach Intell, , 2012. . 34((5):):918--929. . DOI:10.1109/TPAMI.2011.197http://doi.org/10.1109/TPAMI.2011.197..

YC Guo, , , HY Li, , , PX Zhuang. . Underwater image enhancement using a multiscale dense generative adversarial network. . IEEE J Ocean Eng, , 2020. . 45((3):):862--870. . DOI:10.1109/JOE.2019.2911447http://doi.org/10.1109/JOE.2019.2911447..

M Han, , , ZY Lyu, , , T Qiu, , , 等. . A review on intelligence dehazing and color restoration for underwater images. . IEEE Trans Syst Man Cybern Syst, , 2020. . 50((5):):1820--1832. . DOI:10.1109/TSMC.2017.2788902http://doi.org/10.1109/TSMC.2017.2788902..

PL Han, , , F Liu, , , G Zhang, , , 等. . Multi-scale analysis method of underwater polarization imaging. . Acta Phys Sin, , 2018. . 67((5):):054202DOI:10.7498/aps.67.20172009http://doi.org/10.7498/aps.67.20172009..

N Hautière, , , JP Tarel, , , D Aubert, , , 等. . Blind contrast enhancement assessment by gradient ratioing at visible edges. . Image Anal Stereol, , 2008. . 27((2):):87--95. . DOI:10.5566/ias.v27.p87-95http://doi.org/10.5566/ias.v27.p87-95..

KM He, , , J Sun, , , XO Tang. . Single image haze removal using dark channel prior. . Proc IEEE Computer Society Conf on Computer Vision and Pattern Recognition, , 2009. . p.1956--1963. . DOI:10.1109/CVPR.2009.5206515http://doi.org/10.1109/CVPR.2009.5206515..

N He, , , JB Wang, , , LL Zhang, , , 等. . An improved fractional-order differentiation model for image denoising. . Signal Process, , 2015. . 112180--188. . DOI:10.1016/j.sigpro.2014.08.025http://doi.org/10.1016/j.sigpro.2014.08.025..

GJ Hou, , , ZK Pan, , , GD Wang, , , 等. . An efficient nonlocal variational method with application to underwater image restoration. . Neurocomputing, , 2019. . 369106--121. . DOI:10.1016/j.neucom.2019.08.041http://doi.org/10.1016/j.neucom.2019.08.041..

HF Hu, , , L Zhao, , , BJ Huang, , , 等. . Enhancing visibility of polarimetric underwater image by transmittance correction. . IEEE Photon J, , 2017. . 9((3):):6802310DOI:10.1109/JPHOT.2017.2698000http://doi.org/10.1109/JPHOT.2017.2698000..

HF Hu, , , L Zhao, , , XB Li, , , 等. . Underwater image recovery under the nonuniform optical field based on polarimetric imaging. . IEEE Photon J, , 2018. . 10((1):):6900309DOI:10.1109/JPHOT.2018.2791517http://doi.org/10.1109/JPHOT.2018.2791517..

BJ Huang, , , TG Liu, , , HF Hu, , , 等. . Underwater image recovery considering polarization effects of objects. . Opt Expr, , 2016. . 24((9):):9826--9838. . DOI:10.1364/OE.24.009826http://doi.org/10.1364/OE.24.009826..

DM Huang, , , Y Wang, , , W Song, , , 等. . Shallow-water image enhancement using relative global histogram stretching based on adaptive parameter acquisition. . Proc 24th Int Conf on Multimedia Modeling, , 2018. . p.453--465. . DOI:10.1007/978-3-319-73603-7_37http://doi.org/10.1007/978-3-319-73603-7_37..

R Hummel. . Image enhancement by histogram transformation. . Comput Graph Image Process, , 1977. . 6((2):):184--195. . DOI:10.1016/S0146-664X(77)80011-7http://doi.org/10.1016/S0146-664X(77)80011-7..

K Iqbal, , , RA Salam, , , A Osman, , , 等. . Underwater image enhancement using an integrated colour model. . IAENG Int J Comput Sci, , 2007. . 342..

K Iqbal, , , M Odetayo, , , A James, , , 等. . Enhancing the low quality images using unsupervised colour correction method. . IEEE Int Conf on Systems, Man and Cybernetics, , 2010. . p.1703--1709. . DOI:10.1109/ICSMC.2010.5642311http://doi.org/10.1109/ICSMC.2010.5642311..

JS Jaffe. . Computer modeling and the design of optimal underwater imaging systems. . IEEE J Ocean Eng, , 1990. . 15((2):):101--111. . DOI:10.1109/48.50695http://doi.org/10.1109/48.50695..

KR Joshi, , , RS Kamathe. . Quantification of retinex in enhancement of weather degraded images. . Int Conf on Audio, Language and Image Processing, , 2008. . p.1229--1233. . DOI:10.1109/ICALIP.2008.4590120http://doi.org/10.1109/ICALIP.2008.4590120..

R Kapoor, , , R Gupta, , , LH Son, , , 等. . Fog removal in images using improved dark channel prior and contrast limited adaptive histogram equalization. . Multim Tools Appl, , 2019. . 78((16):):23281--23307. . DOI:10.1007/s11042-019-7574-8http://doi.org/10.1007/s11042-019-7574-8..

T Kim, , , M Cha, , , H Kim, , , 等. . Learning to discover cross-domain relations with generative adversarial networks. . Proc 34th Int Conf on Machine Learning, , 2017. . p.1857--1865. . ..

TK Kim, , , JK Paik, , , BS Kang. . Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering. . IEEE Trans Consum Electron, , 1998. . 44((1):):82--87. . DOI:10.1109/30.663733http://doi.org/10.1109/30.663733..

YT Kim. . Contrast enhancement using brightness preserving bi-histogram equalization. . IEEE Trans Consum Electron, , 1997. . 43((1):):1--8. . DOI:10.1109/30.580378http://doi.org/10.1109/30.580378..

EH Land. . The retinex theory of color vision. . Sci Am, , 1977. . 237((6):):108--128. . DOI:10.1038/scientificamerican1277-108http://doi.org/10.1038/scientificamerican1277-108..

Y Lee, , , KB Gibson, , , Z Lee, , , 等. . Stereo image defogging. . Proc IEEE Int Conf on Image Processing, , 2014. . p.5427--5431. . DOI:10.1109/ICIP.2014.7026098http://doi.org/10.1109/ICIP.2014.7026098..

CY Li, , , JC Guo, , , RM Cong, , , 等. . Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior. . IEEE Trans Image Process, , 2016. . 25((12):):5664--5677. . DOI:10.1109/TIP.2016.2612882http://doi.org/10.1109/TIP.2016.2612882..

CY Li, , , JC Guo, , , CL Guo, , , 等. . A hybrid method for underwater image correction. . Patt Recogn Lett, , 2017. . 9462--67. . DOI:10.1016/j.patrec.2017.05.023http://doi.org/10.1016/j.patrec.2017.05.023..

CY Li, , , JC Guo, , , CL Guo. . Emerging from water: underwater image color correction based on weakly supervised color transfer. . IEEE Signal Process Lett, , 2018. . 25((3):):323--327. . DOI:10.1109/LSP.2018.2792050http://doi.org/10.1109/LSP.2018.2792050..

CY Li, , , CL Guo, , , WQ Ren, , , 等. . An underwater image enhancement benchmark dataset and beyond. . IEEE Trans Image Process, , 2019. . 294376--4389. . DOI:10.1109/TIP.2019.2955241http://doi.org/10.1109/TIP.2019.2955241..

CY Li, , , S Anwar, , , F Porikli. . Underwater scene prior inspired deep underwater image and video enhancement. . Patt Recogn, , 2020. . 98107038DOI:10.1016/j.patcog.2019.107038http://doi.org/10.1016/j.patcog.2019.107038..

J Li, , , KA Skinner, , , RM Eustice, , , 等. . WaterGAN: unsupervised generative network to enable real-time color correction of monocular underwater images. . IEEE Robot Autom Lett, , 2018. . 3((1):):387--394. . DOI:10.1109/LRA.2017.2730363http://doi.org/10.1109/LRA.2017.2730363..

YJ Li, , , HM Lu, , , KC Li, , , 等. . Non-uniform de-scattering and de-blurring of underwater images. . Mob Netw Appl, , 2018. . 23((2):):352--362. . DOI:10.1007/s11036-017-0933-7http://doi.org/10.1007/s11036-017-0933-7..

F Liu, , , Y Wei, , , PL Han, , , 等. . Polarization-based exploration for clear underwater vision in natural illumination. . Opt Expr, , 2019. . 27((3):):3629--3641. . DOI:10.1364/OE.27.003629http://doi.org/10.1364/OE.27.003629..

P Liu, , , GY Wang, , , H Qi, , , 等. . Underwater image enhancement with a deep residual framework. . IEEE Access, , 2019. . 794614--94629. . DOI:10.1109/ACCESS.2019.2928976http://doi.org/10.1109/ACCESS.2019.2928976..

TG Liu, , , ZJ Guan, , , XB Li, , , 等. . Polarimetric underwater image recovery for color image with crosstalk compensation. . Opt Lasers Eng, , 2020. . 124105833DOI:10.1016/j.optlaseng.2019.105833http://doi.org/10.1016/j.optlaseng.2019.105833..

M Mangeruga, , , M Cozza, , , F Bruno. . Evaluation of underwater image enhancement algorithms under different environmental conditions. . J Mar Sci Eng, , 2018. . 6((1):):10DOI:10.3390/jmse6010010http://doi.org/10.3390/jmse6010010..

TP Marques, , , AB Albu, , , M Hoeberechts. . A contrast-guided approach for the enhancement of low-lighting underwater images. . J Imag, , 2019. . 5((10):):79DOI:10.3390/jimaging5100079http://doi.org/10.3390/jimaging5100079..

BL McGlamery. . A computer model for underwater camera systems. . Proc SPIE, Ocean Optics VI, , 1980. . 0208221--231. . DOI:10.1117/12.958279http://doi.org/10.1117/12.958279..

K Nomura, , , D Sugimura, , , T Hamamoto. . Underwater image color correction using exposure-bracketing imaging. . IEEE Signal Process Lett, , 2018. . 25((6):):893--897. . DOI:10.1109/LSP.2018.2831630http://doi.org/10.1109/LSP.2018.2831630..

PW Pan, , , F Yuan, , , E Cheng. . Underwater image de-scattering and enhancing using DehazeNet and HWD. . J Mar Sci Technol, , 2018. . 26((4):):531--540. . DOI:10.6119/JMST.201808_26(4).0006http://doi.org/10.6119/JMST.201808_26(4).0006..

PW Pan, , , F Yuan, , , E Cheng. . De-scattering and edge-enhancement algorithms for underwater image restoration. . Front Inform Technol Electron Eng, , 2019. . 20((6):):862--871. . DOI:10.1631/FITEE.1700744http://doi.org/10.1631/FITEE.1700744..

K Panetta, , , C Gao, , , S Agaian. . Human-visual-system-inspired underwater image quality measures. . IEEE J Ocean Eng, , 2016. . 41((3):):541--551. . DOI:10.1109/JOE.2015.2469915http://doi.org/10.1109/JOE.2015.2469915..

YT Peng, , , PC Cosman. . Underwater image restoration based on image blurriness and light absorption. . IEEE Trans Image Process, , 2017. . 26((4):):1579--1594. . DOI:10.1109/TIP.2017.2663846http://doi.org/10.1109/TIP.2017.2663846..

YT Peng, , , XY Zhao, , , PC Cosman. . Single underwater image enhancement using depth estimation based on blurriness. . IEEE Int Conf on Image Processing, , 2015. . p.4952--4956. . DOI:10.1109/ICIP.2015.7351749http://doi.org/10.1109/ICIP.2015.7351749..

YT Peng, , , KM Cao, , , PC Cosman. . Generalization of the dark channel prior for single image restoration. . IEEE Trans Image Process, , 2018. . 27((6):):2856--2868. . DOI:10.1109/TIP.2018.2813092http://doi.org/10.1109/TIP.2018.2813092..

J Perez, , , AC Attanasio, , , N Nechyporenko, , , 等. . A deep learning approach for underwater image enhancement. . Int Work-Conf on the Interplay Between Natural and Artificial Computation, , 2017. . p.183--192. . DOI:10.1007/978-3-319-59773-7_19http://doi.org/10.1007/978-3-319-59773-7_19..

SM Pizer, , , EP Amburn, , , JD Austin, , , 等. . Adaptive histogram equalization and its variations. . Comput Vis Graph Image Process, , 1987. . 39((3):):355--368. . DOI:10.1016/S0734-189X(87)80186-Xhttp://doi.org/10.1016/S0734-189X(87)80186-X..

AJ Raihan, , , PE Abas, , , LC de Silva. . Review of underwater image restoration algorithms. . IET Image Process, , 2019. . 13((10):):1587--1596. . DOI:10.1049/iet-ipr.2019.0117http://doi.org/10.1049/iet-ipr.2019.0117..

WQ Ren, , , SF Liu, , , L Ma, , , 等. . Low-light image enhancement via a deep hybrid network. . IEEE Trans Image Process, , 2019. . 28((9):):4364--4375. . DOI:10.1109/TIP.2019.2910412http://doi.org/10.1109/TIP.2019.2910412..

WQ Ren, , , JS Pan, , , H Zhang, , , 等. . Single image dehazing via multi-scale convolutional neural networks with holistic edges. . Int J Comput Vis, , 2020. . 128((1):):240--259. . DOI:10.1007/s11263-019-01235-8http://doi.org/10.1007/s11263-019-01235-8..

AM Reza. . Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement. . J VLSI Signal Process Syst Signal Image Video Technol, , 2004. . 38((1):):35--44. . DOI:10.1023/B:VLSI.0000028532.53893.82http://doi.org/10.1023/B:VLSI.0000028532.53893.82..

M Roser, , , M Dunbabin, , , A Geiger. . Simultaneous underwater visibility assessment, enhancement and improved stereo. . IEEE Int Conf on Robotics and Automation, , 2014. . p.3840--3847. . DOI:10.1109/ICRA.2014.6907416http://doi.org/10.1109/ICRA.2014.6907416..

YY Schechner, , , Y Averbuch. . Regularized image recovery in scattering media. . IEEE Trans Patt Anal Mach Intell, , 2007. . 29((9):):1655--1660. . DOI:10.1109/TPAMI.2007.1141http://doi.org/10.1109/TPAMI.2007.1141..

YY Schechner, , , N Karpel. . Recovery of underwater visibility and structure by polarization analysis. . IEEE J Ocean Eng, , 2005. . 30((3):):570--587. . DOI:10.1109/JOE.2005.850871http://doi.org/10.1109/JOE.2005.850871..

YY Schechner, , , SG Narasimhan, , , SK Nayar. . Instant dehazing of images using polarization. . Proc IEEE Computer Society Conf on Computer Vision and Pattern Recognition, , 2001. . p.325--332. . DOI:10.1109/CVPR.2001.990493http://doi.org/10.1109/CVPR.2001.990493..

YY Schechner, , , SG Narasimhan, , , SK Nayar. . Polarization-based vision through haze. . Appl Opt, , 2003. . 42((3):):511--525. . DOI:10.1364/AO.42.000511http://doi.org/10.1364/AO.42.000511..

D Singh, , , V Kumar. . A comprehensive review of computational dehazing techniques. . Arch Comput Methods Eng, , 2019. . 26((5):):1395--1413. . DOI:10.1007/s11831-018-9294-zhttp://doi.org/10.1007/s11831-018-9294-z..

W Song, , , Y Wang, , , DM Huang, , , 等. . A rapid scene depth estimation model based on underwater light attenuation prior for underwater image restoration. . Proc 19th Pacific-Rim Conf on Multimedia on Advances in Multimedia Information Processing, , 2018. . p.678--688. . DOI:10.1007/978-3-030-00776-8_62http://doi.org/10.1007/978-3-030-00776-8_62..

C Tang, , , UF von Lukas, , , M Vahl, , , 等. . Efficient underwater image and video enhancement based on retinex. . Signal Image Video Process, , 2019. . 13((5):):1011--1018. . DOI:10.1007/s11760-019-01439-yhttp://doi.org/10.1007/s11760-019-01439-y..

JR Tang, , , NAM Isa. . Bi-histogram equalization using modified histogram bins. . Appl Soft Comput, , 2017. . 5531--43. . DOI:10.1016/j.asoc.2017.01.053http://doi.org/10.1016/j.asoc.2017.01.053..

Y Tian, , , B Liu, , , XY Su, , , 等. . Underwater imaging based on LF and polarization. . IEEE Photon J, , 2019. . 11((1):):6500309DOI:10.1109/JPHOT.2018.2890286http://doi.org/10.1109/JPHOT.2018.2890286..

LA Torres-Méndez, , , G. Dudek. . Color correction of underwater images for aquatic robot inspection. . Proc 5th Int Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, , 2005. . p.60--73. . DOI:10.1007/11585978_5http://doi.org/10.1007/11585978_5..

T Treibitz, , , YY Schechner. . Instant 3Descatter. . Proc IEEE Computer Society Conf on Computer Vision and Pattern Recognition, , 2006. . p.1861--1868. . DOI:10.1109/CVPR.2006.155http://doi.org/10.1109/CVPR.2006.155..

T Treibitz, , , YY Schechner. . Active polarization descattering. . IEEE Trans Patt Anal Mach Intell, , 2009. . 31((3):):385--399. . DOI:10.1109/TPAMI.2008.85http://doi.org/10.1109/TPAMI.2008.85..

T Treibitz, , , YY Schechner. . Turbid scene enhancement using multi-directional illumination fusion. . IEEE Trans Image Process, , 2012. . 21((11):):4662--4667. . DOI:10.1109/TIP.2012.2208978http://doi.org/10.1109/TIP.2012.2208978..

J van de Weijer, , , T Gevers, , , A Gijsenij. . Edge-based color constancy. . IEEE Trans Image Process, , 2007. . 16((9):):2207--2214. . DOI:10.1109/TIP.2007.901808http://doi.org/10.1109/TIP.2007.901808..

KY Wang, , , Y Hu, , , J Chen, , , 等. . Underwater image restoration based on a parallel convolutional neural network. . Remote Sens, , 2019. . 11((13):):1591DOI:10.3390/rs11131591http://doi.org/10.3390/rs11131591..

SQ Wang, , , KD Ma, , , H Yeganeh, , , 等. . A patch-structure representation method for quality assessment of contrast changed images. . IEEE Signal Process Lett, , 2015. . 22((12):):2387--2390. . DOI:10.1109/LSP.2015.2487369http://doi.org/10.1109/LSP.2015.2487369..

Y Wang, , , J Zhang, , , Y Cao, , , 等. . A deep CNN method for underwater image enhancement. . IEEE Int Conf on Image Processing, , 2017. . p.1382--1386. . DOI:10.1109/ICIP.2017.8296508http://doi.org/10.1109/ICIP.2017.8296508..

Y Wang, , , W Song, , , G Fortino, , , 等. . An experimental-based review of image enhancement and image restoration methods for underwater imaging. . IEEE Access, , 2019. . 7140233--140251. . DOI:10.1109/ACCESS.2019.2932130http://doi.org/10.1109/ACCESS.2019.2932130..

YF Wang, , , HY Wang, , , CL Yin, , , 等. . Biologically inspired image enhancement based on retinex. . Neurocomputing, , 2016. . 177373--384. . DOI:10.1016/j.neucom.2015.10.124http://doi.org/10.1016/j.neucom.2015.10.124..

Z Wang, , , AC Bovik. . Modern Image Quality Assessment: Synthesis Lectures on Image, Video, and Multimedia Processing. . Morgan & Claypool, San Rafael, Argentina, , 2006. . p.1--156. . DOI:10.2200/S00010ED1V01Y200508IVM003http://doi.org/10.2200/S00010ED1V01Y200508IVM003..

HC Wen, , , YH Tian, , , TJ Huang, , , 等. . Single underwater image enhancement with a new optical model. . IEEE Int Symp on Circuits and Systems, , 2013. . p.753--756. . DOI:10.1109/ISCAS.2013.6571956http://doi.org/10.1109/ISCAS.2013.6571956..

CC Weng, , , H Chen, , , CS Fuh. . A novel automatic white balance method for digital still cameras. . IEEE Int Symp on Circuits and Systems, , 2005. . p.3801--3804. . DOI:10.1109/ISCAS.2005.1465458http://doi.org/10.1109/ISCAS.2005.1465458..

HD Wu, , , M Zhao, , , FQ Li, , , 等. . Underwater polarization-based single pixel imaging. . J Soc Inform Display, , 2020. . 28((2):):157--163. . DOI:10.1002/jsid.838http://doi.org/10.1002/jsid.838..

K Xie, , , W Pan, , , S Xu. . An underwater image enhancement algorithm for environment recognition and robot navigation. . Robotics, , 2018. . 7((1):):14DOI:10.3390/robotics7010014http://doi.org/10.3390/robotics7010014..

Q Xu, , , ZY Guo, , , QQ Tao, , , 等. . Transmitting characteristics of polarization information under seawater. . Appl Opt, , 2015. . 54((21):):6584--6588. . DOI:10.1364/AO.54.006584http://doi.org/10.1364/AO.54.006584..

HY Yang, , , PY Chen, , , CC Huang, , , 等. . Low complexity underwater image enhancement based on dark channel prior. . 2nd Int Conf on Innovations in Bio-inspired Computing and Applications, , 2011. . p.17--20. . DOI:10.1109/IBICA.2011.9http://doi.org/10.1109/IBICA.2011.9..

M Yang, , , A Sowmya. . An underwater color image quality evaluation metric. . IEEE Trans Image Process, , 2015. . 24((12):):6062--6071. . DOI:10.1109/TIP.2015.2491020http://doi.org/10.1109/TIP.2015.2491020..

M Yang, , , JT Hu, , , CY Li, , , 等. . An in-depth survey of underwater image enhancement and restoration. . IEEE Access, , 2019. . 7123638--123657. . DOI:10.1109/ACCESS.2019.2932611http://doi.org/10.1109/ACCESS.2019.2932611..

KM Yemelyanov, , , SS Lin, , , EN Pugh, , , 等. . Adaptive algorithms for two-channel polarization sensing under various polarization statistics with nonuniform distributions. . Appl Opt, , 2006. . 45((22):):5504--5520. . DOI:10.1364/AO.45.005504http://doi.org/10.1364/AO.45.005504..

GJ Yin, , , B Liu, , , L Sheng, , , 等. . Semantics disentangling for text-to-image generation. . Proc IEEE Conf on Computer Vision and Pattern Recognition, , 2019. . p.2327--2336. . DOI:10.1109/CVPR.2019.00243http://doi.org/10.1109/CVPR.2019.00243..

HF You, , , SW Tian, , , L Yu, , , 等. . Pixel-level remote sensing image recognition based on bidirectional word vectors. . IEEE Trans Geosci Remote Sens, , 2020. . 58((2):):1281--1293. . DOI:10.1109/TGRS.2019.2945591http://doi.org/10.1109/TGRS.2019.2945591..

MK Yuan, , , YX Peng. . Text-to-image synthesis via symmetrical distillation networks. . Proc 26th ACM Int Conf on Multimedia, , 2018. . p.1407--1415. . DOI:10.1145/3240508.3240559http://doi.org/10.1145/3240508.3240559..

MK Yuan, , , YX Peng. . Bridge-GAN: interpretable representation learning for text-to-image synthesis. . IEEE Trans Circ Syst Video Technol, , 2020. . 30((11):):4258--4268. . DOI:10.1109/TCSVT.2019.2953753http://doi.org/10.1109/TCSVT.2019.2953753..

S Zhang, , , T Wang, , , JY Dong, , , 等. . Underwater image enhancement via extended multi-scale retinex. . Neurocomputing, , 2017. . 2451--9. . DOI:10.1016/j.neucom.2017.03.029http://doi.org/10.1016/j.neucom.2017.03.029..

WD Zhang, , , LL Dong, , , XP Pan, , , 等. . Single image defogging based on multi-channel convolutional MSRCR. . IEEE Access, , 2019a. . 772492--72504. . DOI:10.1109/ACCESS.2019.2920403http://doi.org/10.1109/ACCESS.2019.2920403..

WD Zhang, , , LL Dong, , , XP Pan, , , 等. . A survey of restoration and enhancement for underwater images. . IEEE Access, , 2019b. . 7182259--182279. . DOI:10.1109/ACCESS.2019.2959560http://doi.org/10.1109/ACCESS.2019.2959560..

MH Zhao, , , CQ Hu, , , FL Wei, , , 等. . Real-time underwater image recognition with FPGA embedded system for convolutional neural network. . Sensors, , 2019. . 19((2):):350DOI:10.3390/s19020350http://doi.org/10.3390/s19020350..

XW Zhao, , , T Jin, , , S Qu. . Deriving inherent optical properties from background color and underwater image enhancement. . Ocean Eng, , 2015. . 94163--172. . DOI:10.1016/j.oceaneng.2014.11.036http://doi.org/10.1016/j.oceaneng.2014.11.036..

JC Zhou, , , ML Hao, , , DH Zhang, , , 等. . Fusion PSPnet image segmentation based method for multi-focus image fusion. . IEEE Photon J, , 2019a. . 11((6):):6501412DOI:10.1109/JPHOT.2019.2950949http://doi.org/10.1109/JPHOT.2019.2950949..

JC Zhou, , , DG Zhang, , , PY Zou, , , 等. . Retinex-based laplacian pyramid method for image defogging. . IEEE Access, , 2019b. . 7122459--122472. . DOI:10.1109/ACCESS.2019.2934981http://doi.org/10.1109/ACCESS.2019.2934981..

JY Zhu, , , T Park, , , P Isola, , , 等. . Unpaired image-to-image translation using cycle-consistent adversarial networks. . Proc IEEE Int Conf on Computer Vision, , 2017. . p.2223--2232. . DOI:10.1109/ICCV.2017.244http://doi.org/10.1109/ICCV.2017.244..

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

暂无数据