An approach to underwater image enhancement based on image structural decomposition

被引:13
|
作者
Ji Tingting [1 ]
Wang Guoyu [1 ]
机构
[1] Ocean Univ China, Coll Informat Sci & Engn, Qingdao 266100, Peoples R China
基金
中国国家自然科学基金;
关键词
underwater image; image structural decomposition; image enhancement; retinex; RETINEX;
D O I
10.1007/s11802-015-2426-2
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium. Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image structural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and structure components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the enhanced structure and preserved detail component are recomposed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.
引用
收藏
页码:255 / 260
页数:6
相关论文
共 50 条
  • [31] Underwater Optical Image Enhancement Based on Dominant Feature Image Fusion
    Lin Sen
    Chi Kai-chen
    Li Wen-tao
    Tang Yan-dong
    ACTA PHOTONICA SINICA, 2020, 49 (03)
  • [32] Space Object Image Enhancement Based on Intrinsic Image Decomposition
    Yao, Yuan
    Jiang, Zhiguo
    Zhang, Haopeng
    Shi, Jun
    2015 IEEE AEROSPACE CONFERENCE, 2015,
  • [33] An image enhancement algorithm for turbid underwater image based on multiple methods
    Wang, Hao
    Han, Bin
    Du, Zihao
    Wang, Sheng
    Zhang, Ziquan
    Liu, Qi
    Zhang, Yi
    PROCEEDINGS OF 2020 5TH INTERNATIONAL CONFERENCE ON MULTIMEDIA AND IMAGE PROCESSING (ICMIP 2020), 2020, : 67 - 71
  • [34] RUDIE: Robust approach for underwater digital image enhancement
    Reddy, V.Sidda
    Reddy, G.Ravi Shankar
    Reddy, K.Sivanagi
    Journal of Electronic Science and Technology, 2024, 22 (04)
  • [35] UNDERWATER IMAGE ENHANCEMENT BASED ON LINEAR IMAGE INTERPOLATION AND LIMITED IMAGE ENHANCER TECHNIQUES
    Bindhu, A.
    Maheswari, Uma O.
    2017 FOURTH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATION AND NETWORKING (ICSCN), 2017,
  • [36] RUDIE:Robust approach for underwater digital image enhancement
    VSidda Reddy
    GRavi Shankar Reddy
    KSivanagi Reddy
    Journal of Electronic Science and Technology, 2024, 22 (04) : 98 - 110
  • [37] A Two-Step Approach for Underwater Image Enhancement
    Wei, Donghui
    Chen, Wanchun
    Chen, Xiaogang
    2017 INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS, ELECTRONICS AND CONTROL (ICCSEC), 2017, : 985 - 988
  • [38] Underwater image enhancement with image colorfulness measure
    Yang, Xi
    Li, Hui
    Chen, Rong
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2021, 95
  • [39] Underwater image enhancement with image colorfulness measure
    Yang, Xi
    Li, Hui
    Chen, Rong
    Signal Processing: Image Communication, 2021, 95
  • [40] Underwater Image Enhancement Using Image Processing
    Nagamma, V.
    Halse, S. V.
    THIRD INTERNATIONAL CONFERENCE ON IMAGE PROCESSING AND CAPSULE NETWORKS (ICIPCN 2022), 2022, 514 : 13 - 22