Underwater image restoration based on diffraction bounded optimization algorithm with dark channel prior

被引:20
|
作者
Mathias, Ajisha [1 ]
Samiappan, Dhanalakshmi [1 ]
机构
[1] SRM Inst Sci & Technol, Kattankulathur, Tamil Nadu, India
来源
OPTIK | 2019年 / 192卷
关键词
Diffraction; Image restoration; Turbulence removal; Super-resolution; COLOR; ENHANCEMENT; MODEL;
D O I
10.1016/j.ijleo.2019.06.025
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The restoration of underwater images is challenging due to the turbid nature of water. The effects of diffraction due to the varying refractive index of water medium, absorption and scattering properties of water and the distance between the image spot to the camera, can lead to geometric distortions and blur. Many algorithms exist so far to restore the quality of underwater images. The effect of turbulence in underwater scenarios areas are challenging for most restoration algorithms. Although the metric gauge for the restoration of the underwater scene is still under evaluation, a new algorithm based on the Diffraction Bounded Image Formation Model (DB-IFM) is proposed. The diffraction correction restores the image based on the diffraction-bounded restoration. The dark channel of the image assessed with various transmission maps based on Dark Channel Prior (DCP) algorithm. For a broad set of data with varying luminance, the outcomes are looked at both subjectively and quantitatively by enhanced restoration.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Underwater image restoration based on improved dark channel prior
    Wang, Yingbo
    Cao, Jie
    Tang, Mingyuan
    Li, Guoliang
    Hao, Qun
    Fang, Yami
    SEVENTH SYMPOSIUM ON NOVEL PHOTOELECTRONIC DETECTION TECHNOLOGY AND APPLICATIONS, 2021, 11763
  • [2] GUDCP: Generalization of Underwater Dark Channel Prior for Underwater Image Restoration
    Liang, Zheng
    Ding, Xueyan
    Wang, Yafei
    Yan, Xiaohong
    Fu, Xianping
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 32 (07) : 4879 - 4884
  • [3] Efficient underwater image restoration utilizing modified dark channel prior
    Fayaz, Sheezan
    Parah, Shabir A.
    Qureshi, G. J.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (10) : 14731 - 14753
  • [4] Underwater image restoration by red channel compensation and underwater median dark channel prior
    Zhou, Jingchun
    Liu, Dingshuo
    Xie, Xiong
    Zhang, Weishi
    APPLIED OPTICS, 2022, 61 (10) : 2915 - 2922
  • [5] A novel dark channel prior guided variational framework for underwater image restoration
    Hou, Guojia
    Li, Jingming
    Wang, Guodong
    Yang, Huan
    Huang, Baoxiang
    Pan, Zhenkuan
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2020, 66
  • [6] Generalization of the Dark Channel Prior for Single Image Restoration
    Peng, Yan-Tsung
    Cao, Keming
    Cosman, Pamela C.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (06) : 2856 - 2868
  • [7] Efficient underwater image restoration utilizing modified dark channel prior
    Sheezan Fayaz
    Shabir A. Parah
    G. J. Qureshi
    Multimedia Tools and Applications, 2023, 82 : 14731 - 14753
  • [8] Underwater optical image processing based on double threshold judgements and optimized red dark channel prior method
    Wu, Qi
    Guo, YinJing
    Hou, JiaChen
    Yuan, JiaoJiao
    Kong, Fang
    Lyu, WenHong
    Liu, Zhen
    Yang, WenJian
    Liang, QuanQuan
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (19) : 29985 - 30002
  • [9] VARIATIONAL IMAGE DEHAZING WITH A NOVEL UNDERWATER DARK CHANNEL PRIOR
    Jin, Zhengmeng
    Ma, Yue
    Min, Lihua
    Zheng, Minling
    INVERSE PROBLEMS AND IMAGING, 2025, 19 (02) : 334 - 354
  • [10] VARIATIONAL IMAGE DEHAZING WITH A NOVEL UNDERWATER DARK CHANNEL PRIOR
    Jin, Zhengmeng
    Ma, Yue
    Min, Lihua
    Zheng, Minling
    INVERSE PROBLEMS AND IMAGING, 2024,