L2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion

被引:79
|
作者
Marques, Tunai Porto [1 ]
Albu, Alexandra Branzan [1 ]
机构
[1] Univ Victoria, Victoria, BC, Canada
关键词
D O I
10.1109/CVPRW50498.2020.00277
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Images captured underwater often suffer from sub-optimal illumination settings that can hide important visual features, reducing their quality. We present a novel single-image low-light underwater image enhancer, (LUWE)-U-2, that builds on our observation that an efficient model of atmospheric lighting can be derived from local contrast information. We create two distinct models and generate two enhanced images from them: one that highlights finer details, the other focused on darkness removal. A multi-scale fusion process is employed to combine these images while emphasizing regions of higher luminance, saliency and local contrast. We demonstrate the performance of (LUWE)-U-2 by using seven metrics to test it against seven state-of-the-art enhancement methods specific to underwater and low-light scenes.
引用
收藏
页码:2286 / 2295
页数:10
相关论文
共 50 条
  • [1] Multi-Scale Progressive Fusion Network for Low-Light Image Enhancement
    Zhang, Hongxin
    Ran, Teng
    Xiao, Wendong
    Lv, Kai
    Peng, Song
    Yuan, Liang
    Wang, Jingchuan
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2025, 74
  • [2] A novel multi-scale fusion framework for detail-preserving low-light image enhancement
    Xu, Yadong
    Yang, Cheng
    Sun, Beibei
    Yan, Xiaoan
    Chen, Minglong
    INFORMATION SCIENCES, 2021, 548 : 378 - 397
  • [3] Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion
    Gao, Farong
    Wang, Kai
    Yang, Zhangyi
    Wang, Yejian
    Zhang, Qizhong
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (02) : 1 - 17
  • [4] Multiscale Fusion Method for the Enhancement of Low-Light Underwater Images
    Zhou, Jingchun
    Zhang, Dehuan
    Zhang, Weishi
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
  • [5] Multi-scale wavelet feature fusion network for low-light image enhancement
    Wei, Ran
    Wei, Xinjie
    Xia, Shucheng
    Chang, Kan
    Ling, Mingyang
    Nong, Jingxiang
    Xu, Li
    COMPUTERS & GRAPHICS-UK, 2025, 127
  • [6] Visual Enhancement of Underwater Images Using Transmission Estimation and Multi-Scale Fusion
    Anandh, R. Vijay
    Devi, S. Rukmani
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2023, 44 (03): : 1897 - 1910
  • [7] Underwater image enhancement via multi-scale fusion and adaptive color-gamma correction in low-light conditions
    Zhang, Dan
    He, Zongxin
    Zhang, Xiaohuan
    Wang, Zhen
    Ge, Wenyi
    Shi, Taian
    Lin, Yi
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, 126
  • [8] Low-light image enhancement based on multi-illumination estimation and multi-scale fusion
    Xin’ai Zhang
    Jing Gao
    Kaiming Nie
    Tao Luo
    Optoelectronics Letters, 2025, 21 (6) : 362 - 369
  • [9] MULTI-SCALE FEATURE GUIDED LOW-LIGHT IMAGE ENHANCEMENT
    Guo, Lanqing
    Wan, Renjie
    Su, Guan-Ming
    Kot, Alex C.
    Wen, Bihan
    2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2021, : 554 - 558
  • [10] Attention-Guided Multi-Scale Feature Fusion Network for Low-Light Image Enhancement
    Cui, HengShuai
    Li, Jinjiang
    Hua, Zhen
    Fan, Linwei
    FRONTIERS IN NEUROROBOTICS, 2022, 16