Advanced Search
Volume 43 Issue 2
Feb.  2021
Turn off MathJax
Article Contents
Yinjing GUO, Qi WU, Jiaojiao YUAN, Jiachen HOU, Wenhong LÜ. Research Progress on Underwater Optical Image Processing[J]. Journal of Electronics & Information Technology, 2021, 43(2): 426-435. doi: 10.11999/JEIT190803
Citation: Yinjing GUO, Qi WU, Jiaojiao YUAN, Jiachen HOU, Wenhong LÜ. Research Progress on Underwater Optical Image Processing[J]. Journal of Electronics & Information Technology, 2021, 43(2): 426-435. doi: 10.11999/JEIT190803

Research Progress on Underwater Optical Image Processing

doi: 10.11999/JEIT190803
Funds:  The National Natural Science Foundation of China (61471224), Shandong Province Key Research and Development Program (Special Project for Public Welfare) (2018GHY115022)
  • Received Date: 2019-10-16
  • Rev Recd Date: 2020-02-28
  • Available Online: 2020-12-11
  • Publish Date: 2021-02-23
  • Underwater optical image processing is an important basis for underwater equipment to complete deep-sea exploration and operation tasks. Based on a brief description of the research background, significance and hotspots of underwater optical image processing, this paper gives a detailed overview of underwater imaging technology and clearness of underwater images from the aspects of improving the lighting factors and color correction of underwater images. The research progress focuses on the research status of the two most active research directions of image restoration methods and image enhancement methods based on imaging models. According to the research hotspots of underwater optical image processing, the research of underwater optical image processing is prospected from the perspectives of considering the forward refraction of light, combining underwater imaging models and image enhancement algorithms, introducing new algorithms in related fields, and improving the real-time performance of image processing.

  • loading
  • BONIN F, BURGUERA A, and OLIVER G. Imaging systems for advanced underwater vehicles[J]. Journal of Maritime Research, 2011, 8(1): 65–86.
    SCHECHNER Y Y and KARPEL N. Clear underwater vision[C]. The 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, USA, 2004: 89–97. doi: 10.1109/CVPR.2004.1315078.
    LU Huimin, LI Yujie, and SERIKAWA S. Computer Vision for Ocean Observing[M]. Artificial Intelligence and Computer Vision. Cham: Springer, 2017, 672: 1–16. doi: 10.1007/978-3-319-46245-5_1.
    张莉云. 水下图像清晰化算法研究[D]. [硕士论文], 天津大学, 2017.

    ZHANG Liyun. Research on visibility enhancement of underwater images[D]. [Master dissertation], Tianjin University, 2017.
    冷洁. 水下光学成像系统的研究现状和展望[J]. 激光杂志, 2008, 29(1): 7–8. doi: 10.3969/j.issn.0253-2743.2008.01.003

    LENG Jie. The investigation and prospect of underwater imaging system[J]. Laser Journal, 2008, 29(1): 7–8. doi: 10.3969/j.issn.0253-2743.2008.01.003
    FOURNIER G R, BONNIER D, FORAND J L, et al. LUCIE ROV-mounted laser imaging system[C]. Ocean Optics XI, San Diego, USA, 1992, 1750: 443–452. doi: 10.1117/12.140673.
    FOURNIER G R, BONNIER D, FORAND J L, et al. Range-gated underwater laser imaging system[J]. Optical Engineering, 1993, 32(9): 2185–2190. doi: 10.1117/12.143954
    WEIDEMANN A, FOURNIER G R, FORAND L, et al. In harbor underwater threat detection/identification using active imaging[C]. Photonics for Port and Harbor Security, Orlando, USA, 2005: 59–70. doi: 10.1117/12.603601.
    TAN C S, SLUZEK A, and SEET G G L. Model of gated imaging in turbid media[J]. Optical Engineering, 2005, 44(11): 116002. doi: 10.1117/1.2124567
    TAN C S, SLUZEK A, SEET GL G, et al. Range gated imaging system for underwater robotic vehicle[C]. OCEANS 2006-Asia Pacific, Singapore, 2007: 1–6. doi: 10.1109/oceansap.2006.4393938.
    MINOR L G. Dual mode semi-active laser/laser radar seeker[P]. US, 6262800, 2001.
    JAFFE J S. Development of a laser line scan LIDAR imaging system for AUV use[R]. Award Number: N00014-09-1-0477, 2010.
    CARIOU J, LE JEUNE B, LOTRIAN J, et al. Polarization effects of seawater and underwater targets[J]. Applied Optics, 1990, 29(11): 1689–1695. doi: 10.1364/ao.29.001689
    曹念文, 刘文清, 张玉钧. 偏振成像技术提高成像清晰度、成像距离的定量研究[J]. 物理学报, 2000, 49(1): 61–66. doi: 10.3321/j.issn:1000-3290.2000.01.014

    CAO Nianwen, LIU Wenqing, and ZHANG Yujun. Quantitative study of improvements of the imaging contrast and imaging range by the polarization technique[J]. Acta Physica Sinica, 2000, 49(1): 61–66. doi: 10.3321/j.issn:1000-3290.2000.01.014
    CRONIN T W, SHASHAR N, CALDWELL R L, et al. Polarization vision and its role in biological signaling[J]. Integrative and Comparative Biology, 2003, 43(4): 549–558. doi: 10.1093/icb/43.4.549
    TREIBITZ T and SCHECHNER Y Y. Active polarization descattering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(3): 385–399. doi: 10.1109/TPAMI.2008.85
    SCHECHNER Y Y and AVERBUCH Y. Regularized image recovery in scattering media[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(9): 1655–1660. doi: 10.1109/tpami.2007.1141
    ARNOLD-BOS A, MALKASSE J P, and KERVERN G. Towards a model-free denoising of underwater optical images[C]. Europe Oceans 2005, Brest, France, 2005: 527–532. doi: 10.1109/oceanse.2005.1511770.
    TREIBITZ T and SCHECHNER Y Y. Turbid scene enhancement using multi-directional illumination fusion[J]. IEEE Transactions on Image Processing, 2012, 21(11): 4662–4667. doi: 10.1109/TIP.2012.2208978
    HARDY K, CAMERON J, HERBST L, et al. Hadal landers: The DEEPSEA CHALLENGE ocean trench free vehicles[C]. 2013 OCEANS - San Diego, San Diego, USA, 2013: 1–10.
    ROSER M, DUNBABIN M, and GEIGER A. Simultaneous underwater visibility assessment, enhancement and improved stereo[C]. 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014: 3840–3847. doi: 10.1109/icra.2014.6907416.
    GARCIA R, NICOSEVICI T, and CUFI X. On the way to solve lighting problems in underwater imaging[C]. OCEANS’02 MTS/IEEE, Biloxi, USA, 2002: 1018–1024. doi: 10.1109/oceans.2002.1192107.
    JIANG Qin, WANG Guoyu, GONG Benxing, et al. A novel approach to underwater de-scattering based on sparse and low-rank matrix decomposition[C]. OCEANS - MTS/IEEE Kobe Techno-Oceans, Kobe, Japan, 2018: 1–4. doi: 10.1109/oceanskobe.2018.85591.
    PAN Panwang, YUAN Fei, and CHENG En. Underwater image de-scattering and enhancing using dehazenet and HWD[J]. Journal of Marine Science and Technology, 2018, 26(4): 531–540.
    LU Huimin, LI Yujie, UEMURA T, et al. Low illumination underwater light field images reconstruction using deep convolutional neural networks[J]. Future Generation Computer Systems, 2018, 82: 142–148. doi: 10.1016/j.future.2018.01.001
    LI Yujie, LU Huimin, LI K C, et al. Non-uniform de-scattering and de-blurring of underwater images[J]. Mobile Networks and Applications, 2018, 23(2): 352–362. doi: 10.1007/s11036-017-0933-7
    张颢, 范新南, 李敏, 等. 基于光学成像模型的水下图像超分辨率重构[J]. 计算机与现代化, 2017(4): 7–13. doi: 10.3969/j.issn.1006-2475.2017.04.002

    ZHANG Hao, FAN Xinnan, LI Min, et al. Underwater image super-resolution reconstruction based on optical imaging model[J]. Computer and Modernization, 2017(4): 7–13. doi: 10.3969/j.issn.1006-2475.2017.04.002
    王鑫, 朱行成, 宁晨, 等. 融合暗原色先验和稀疏表示的水下图像复原[J]. 电子与信息学报, 2018, 40(2): 264–271. doi: 10.11999/jeit170381

    WANG Xin, ZHU Xingcheng, NING Chen, et al. Combination of dark-channel prior with sparse representation for underwater image restoration[J]. Journal of Electronics &Information Technology, 2018, 40(2): 264–271. doi: 10.11999/jeit170381
    PAN Panwang, YUAN Fei, and CHENG En. De-scattering and edge-enhancement algorithms for underwater image restoration[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 862–871.
    ANCUTI C, ANCUTI C O, HABER T, et al. Enhancing underwater images and videos by fusion[C]. IEEE Conference on Computer Vision and Pattern Recognition, Providence, USA, 2012: 81–88. doi: 10.1109/cvpr.2012.6247661.
    TAO Li and ASARI V K. Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images[J]. Journal of Electronic Imaging, 2005, 14(4): 043006. doi: 10.1117/1.2136903
    PADMAVATHI G, SUBASHINI P, KUMAR M M, et al. Comparison of filters used for underwater image pre-processing[J]. International Journal of Computer Science and Network Security, 2010, 10(1): 58–65.
    王彬. 基于改进等功率谱法的水下图像增强[J]. 中国科技信息, 2009(19): 46–47. doi: 10.3969/j.issn.1001-8972.2009.19.017

    WANG Bin. Underwater image enhancement based on improved equal power spectral method[J]. China Science and Technology Information, 2009(19): 46–47. doi: 10.3969/j.issn.1001-8972.2009.19.017
    汪荣贵, 朱静, 杨万挺, 等. 基于照度分割的局部多尺度Retinex算法[J]. 电子学报, 2010, 38(5): 1181–1186.

    WANG Ronggui, ZHU Jing, YANG Wanting, et al. An improved local multi-scale Retinex algorithm based on illuminance image segmentation[J]. Acta Electronica Sinica, 2010, 38(5): 1181–1186.
    李庆忠, 李长顺, 王中琦. 基于小波变换的水下降质图像复原算法[J]. 计算机工程, 2011, 37(22): 202–203, 206. doi: 10.3969/j.issn.1000-3428.2011.22.067

    LI Qingzhong, LI Changshun, and WANG Zhongqi. Restoration algorithm for degraded underwater image based on wavelet transform[J]. Computer Engineering, 2011, 37(22): 202–203, 206. doi: 10.3969/j.issn.1000-3428.2011.22.067
    郭相凤, 贾建芳, 杨瑞峰, 等. 基于水下图像光学成像模型的清晰化算法[J]. 计算机应用, 2012, 32(10): 2836–2839. doi: 10.3724/SP.J.1087.2012.02836

    GUO Xiangfeng, JIA Jianfang, YANG Ruifeng, et al. Visibility enhancing algorithm based on optical imaging model for underwater images[J]. Journal of Computer Application, 2012, 32(10): 2836–2839. doi: 10.3724/SP.J.1087.2012.02836
    ZHOU Jianjun and ZHOU Fugen. Single image dehazing motivated by Retinex theory[C]. The 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation, Toronto, Canada, 2013: 243–247.
    IQBAL K, SALAM R A, OSMAN A, et al. Underwater image enhancement using an integrated colour model[J]. International Journal of Computer Science, 2007, 34(2): 239–244.
    徐岩, 马硕, 王权威. 一种利用前景模型的水下图像增强算法[J]. 小型微型计算机系统, 2017, 38(12): 2802–2806. doi: 10.3969/j.issn.1000-1220.2017.12.033

    XU Yan, MA Shuo, and WANG Quanwei. Underwater image enhancement algorithm using foreground modeling[J]. Journal of Chinese Computer Systems, 2017, 38(12): 2802–2806. doi: 10.3969/j.issn.1000-1220.2017.12.033
    LI Yujie, LU Huimin, LI Jianru, et al. Underwater image de-scattering and classification by deep neural network[J]. Computers & Electrical Engineering, 2016, 54: 68–77. doi: 10.1016/j.compeleceng.2016.08.008
    CHIANG J Y and CHEN Yingching. Underwater image enhancement by wavelength compensation and dehazing[J]. IEEE Transactions on Image Processing, 2012, 21(4): 1756–1769. doi: 10.1109/tip.2011.2179666
    汤忠强, 周波, 戴先中, 等. 基于改进DCP算法的水下机器人视觉增强[J]. 机器人, 2018, 40(2): 222–230. doi: 10.13973/j.cnki.robot.170251

    TANG Zhongqiang, ZHOU Bo, DAI Xianzhong, et al. Underwater robot visual enhancements based on the improved DCP algorithm[J]. Robot, 2018, 40(2): 222–230. doi: 10.13973/j.cnki.robot.170251
    FU Xueyang, ZHUANG Peixian, HUANG Yue, et al. A retinex-based enhancing approach for single underwater image[C]. IEEE International Conference on Image Processing (ICIP), Paris, France, 2014: 4572–4576. doi: 10.1109/icip.2014.7025927.
    TANG Chong, VON LUKAS U F, VAHL M, et al. Efficient underwater image and video enhancement based on Retinex[J]. Signal, Image and Video Processing, 2019, 13(5): 1011–1018. doi: 10.1007/s11760-019-01439-y
    杨爱萍, 张莉云, 曲畅, 等. 基于加权L1正则化的水下图像清晰化算法[J]. 电子与信息学报, 2017, 39(3): 626–633. doi: 10.11999/JEIT160481

    YANG Aiping, ZHANG Liyun, QU Chang, et al. Underwater images visibility improving algorithm with weighted L1 regularization[J]. Journal of Electronics &Information Technology, 2017, 39(3): 626–633. doi: 10.11999/JEIT160481
    LIU Peng, WANG Guoyu, QI Hao, et al. Underwater image enhancement with a deep residual framework[J]. IEEE Access, 2019, 7: 94614–94629. doi: 10.1109/access.2019.2928976
    GAO Bingshao, ZHANG Ming, ZHAO Qian, et al. Underwater image enhancement using adaptive retinal mechanisms[J]. IEEE Transactions on Image Processing, 2019, 28(11): 5580–5595. doi: 10.1109/TIP.2019.2919947
    杨爱萍, 郑佳, 王建, 等. 基于颜色失真去除与暗通道先验的水下图像复原[J]. 电子与信息学报, 2015, 37(11): 2541–2547. doi: 10.11999/JEIT150483

    YANG Aiping, ZHENG Jia, WANG Jian, et al. Underwater image restoration based on color cast removal and dark channel prior[J]. Journal of Electronics &Information Technology, 2015, 37(11): 2541–2547. doi: 10.11999/JEIT150483
    胡学龙, 张文, 胡铸鑫, 等. 一种改进的暗通道先验水下彩色图像复原算法[J]. 扬州大学学报: 自然科学版, 2018, 21(4): 37–41. doi: 10.19411/j.1007-824x.2018.04.009

    HU Xuelong, ZHANG Wen, HU Zhuxin, et al. Underwater color image restoration algorithm based on improved prior dark-channel model[J]. Journal of Yangzhou University:Natural Science Edition, 2018, 21(4): 37–41. doi: 10.19411/j.1007-824x.2018.04.009
    王国霖, 田建东, 李鹏越. 基于双透射率水下成像模型的图像颜色校正[J]. 光学学报, 2019, 39(9): 0901002. doi: 10.3788/AOS201939.0901002

    WANG Guolin, TIAN Jiandong, and LI Pengyue. Image color correction based on double transmission underwater imaging model[J]. Acta Optica Sinica, 2019, 39(9): 0901002. doi: 10.3788/AOS201939.0901002
    WEN Haocheng, TIAN Yonghong, HUANG Tiejun, et al. Single underwater image enhancement with a new optical model[C]. IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, China, 2013: 753–756. doi: 10.1109/iscas.2013.6571956.
    GALDRAN A, PARDO D, PICÓN A, et al. Automatic red-channel underwater image restoration[J]. Journal of Visual Communication and Image Representation, 2015, 26: 132–145. doi: 10.1016/j.jvcir.2014.11.006
    蒋泽新, 朴燕. 基于电磁理论的水下图像色彩补偿[J]. 激光与光电子学进展, 2018, 55(8): 081006. doi: 10.3788/LOP55.081006

    JIANG Zexin and PIAO Yan. Underwater image color compensation based on electromagnetic theory[J]. Laser &Optoelectronics Progress, 2018, 55(8): 081006. doi: 10.3788/LOP55.081006
    杨爱萍, 曲畅, 王建, 等. 基于水下成像模型的图像清晰化算法[J]. 电子与信息学报, 2018, 40(2): 298–305. doi: 10.11999/JEIT170460

    YANG Aiping, QU Chang, WANG Jian, et al. Underwater image visibility restoration based on underwater imaging model[J]. Journal of Electronics &Information Technology, 2018, 40(2): 298–305. doi: 10.11999/JEIT170460
    WANG Keyan, HU Yan, CHEN Jun, et al. Underwater image restoration based on a parallel convolutional neural network[J]. Remote Sensing, 2019, 11(13): 1591. doi: 10.3390/rs11131591
    ZHOU Linan, XIAO Yin, and CHEN Wen. Imaging through turbid media with vague concentrations based on cosine similarity and convolutional neural network[J]. IEEE Photonics Journal, 2019, 11(4): 7801315. doi: 10.1109/JPHOT.2019.2927746
    LI Chongyi, GUO Jichang, and GUO Chunle. Emerging from water: underwater image color correction based on weakly supervised color transfer[J]. IEEE Signal Processing Letters, 2018, 25(3): 323–327. doi: 10.1109/LSP.2018.2792050
    CHEN Xingyu, YU Junzhi, KONG Shihan, et al. Towards real-time advancement of underwater visual quality with GAN[J]. IEEE Transactions on Industrial Electronics, 2019, 66(12): 9350–9359. doi: 10.1109/TIE.2019.2893840
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(3)

    Article Metrics

    Article views (2147) PDF downloads(437) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return