Sea surface target image enhancement method based on separable reflection and refraction

被引:0
|
作者
Wang, Jialin [1 ]
Duan, Jin [1 ]
Xie, Guofang [1 ]
Fang, Ruisen [1 ]
Zhu, Wenbo [2 ]
Fu, Weijie [2 ]
机构
[1] Changchun Univ Sci & Technol, Sch Elect & Informat Engn, Changchun 130012, Peoples R China
[2] Foshan Univ, Sch Mechatron Engn & Automat, Foshan 528001, Peoples R China
来源
OPTICS AND LASER TECHNOLOGY | 2025年 / 181卷
基金
中国国家自然科学基金;
关键词
Sun glint; Polarization characteristics; Separable reflection and refraction; Polarization orthogonal decomposition; Image enhancement; POLARIZATION CHARACTERISTICS; VISIBILITY; GLINTS;
D O I
10.1016/j.optlastec.2024.112012
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In marine target detection, sun glint is a strong source of interference, which causes a large area of pixel saturation during imaging, making it difficult to effectively distinguish between the target and the sea surface background. To address the problem of sun glint interfering with target imaging, we first simulate and analyze the multi-angle polarization characteristics of rough sea surface seawater according to the Cox-Munk rough sea surface probabilistic statistical model. Secondly, we propose the constraints that the refracted light information of seawater can be effectively separated at the near-horizontal observation zenith angle, and the polarization orthogonal decomposition principle is utilized to realize the separation of reflected and refracted light of seawater. Finally, we refer to the underwater imaging model and propose an equivalent model of target imaging under sun glint interference. The light intensity information of the sea surface background and the target is equivalently replaced by the light intensity information of the reflected and refracted light of seawater, which further solves the target image without the interference of sun glint. The results show that our method not only realizes the enhancement of the target image based on the suppression of the sea surface sun glint, but also preserves the texture information of the sea surface. The method is of great practical significance for the search and rescue of people overboard as well as the monitoring of marine ecological environment.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] A method for image enhancement based on light compensation
    Jiang, Yong-Xin
    Wang, Xiao-Tong
    Xu, Xiao-Gang
    Huang, Hua
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2009, 37 (SUPPL.): : 151 - 155
  • [32] Linear Prediction based Image Enhancement Method
    Albu, Felix
    2015 IEEE 5TH INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - BERLIN (ICCE-BERLIN), 2015, : 496 - 499
  • [33] An Image Enhancement Method Based On Genetic Algorithm
    Hashemi, Sara
    Kiani, Soheila
    Noroozi, Navid
    Moghaddam, Mohsen Ebrahimi
    ICDIP 2009: INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING, PROCEEDINGS, 2009, : 167 - 171
  • [34] A study on Retinex Based method for Image Enhancement
    Parihar, Anil Singh
    Singh, Kavinder
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INVENTIVE SYSTEMS AND CONTROL (ICISC 2018), 2018, : 619 - 624
  • [35] Image Enhancement Method Based on Deep Learning
    Zhang, Peipei
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [36] A Method of Image Enhancement Based on Wavelet Transform
    Hu Youbin
    Chen Baihua
    Wan Wenhui
    Liu Zhiming
    Wang Chengjian
    ICCSE 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, 2008, : 848 - 850
  • [37] Image enhancement method based on wavelet transform
    Xu, B
    Fu, CY
    Ma, JG
    HYBRID IMAGE AND SIGNAL PROCESSING VII, 2000, 4044 : 150 - 157
  • [38] Nighttime Image Stitching Method Based on Image Decomposition Enhancement
    Yan, Mengying
    Qin, Danyang
    Zhang, Gengxin
    Tang, Huapeng
    Ma, Lin
    ENTROPY, 2023, 25 (09)
  • [39] A SAR Target Image Simulation Method With DNN Embedded to Calculate Electromagnetic Reflection
    Niu, Shengren
    Qiu, Xiaolan
    Lei, Bin
    Fu, Kun
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 14 : 2593 - 2610
  • [40] Image enhancement based on a nonlinear multiscale method
    Sattar, F
    Floreby, L
    Salomonsson, G
    Lovstrom, B
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (06) : 888 - 895