Deep-Sea Image Enhancement Using Multi-Scale Retinex with Reverse Color Loss For Autonomous Underwater Vehicles

被引:0
|
作者
Mercado, Marie Angelyn [1 ]
Ishii, Kazuo [1 ]
Ahn, Jonghyun [2 ]
机构
[1] Kyushu Inst Technol, Dept Human Intelligence Syst, Kitakyushu, Fukuoka, Japan
[2] Kyushu Inst Technol, Ctr Sociorobot Synth, Kitakyushu, Fukuoka, Japan
来源
关键词
deep-sea optical imaging; image enhancement; Retinex model; Beer-Lambert Law;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Advances on underwater optical imaging has been rampant recently because of numerous applications it offers and the increasing use of underwater vehicles. Unfortunately, due to the inherent property of light in water, images tend to be hazy, have non-uniform illumination and colors get distorted. Retinex algorithms were formulated for dynamic range compression and tonal rendition to fix the illumination and color distortion problem. Multi-scale Retinex, an extension of the original Retinex algorithm, has been proven to enhance images. However, Retinex Theory is based on human visual system in air medium. Due to this, light attenuation is not considered. Through Beer-Lambert Law, the light attenuation percentage can be estimated and added back to the original image in a process the researchers call Reverse Color Loss. Thus, combining Multi-scale Retinex and Reverse Color Loss, an enhancement algorithm for deep-sea application for the use of AUVs is proposed.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Autonomous underwater robot for underwater image enhancement via multi-scale deformable convolution network with attention mechanism
    Lin, Yi
    Zhou, Jingchun
    Ren, Wenqi
    Zhang, Weishi
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 191
  • [42] A simulation environment for deep-sea hydrothermal plume tracing with autonomous underwater vehicles
    Tian, Yu
    Li, Wei
    Zhang, Aiqun
    Jiqiren/Robot, 2012, 34 (02): : 159 - 169
  • [43] Color Image Fusion Method Using the Multi-Scale Retinex and Directional Support Value Transform
    Xie, Yaocheng
    Zheng, Sheng
    Guo, Cuimei
    Hao, Wei
    MIPPR 2011: MULTISPECTRAL IMAGE ACQUISITION, PROCESSING, AND ANALYSIS, 2011, 8002
  • [44] Image shadow removal via multi-scale deep Retinex decomposition
    Huang, Yan
    Lu, Xinchang
    Quan, Yuhui
    Xu, Yong
    Ji, Hui
    PATTERN RECOGNITION, 2025, 159
  • [45] Investigating the relationship between image enhancement and image compression in the context of the multi-scale retinex
    Rahman, Zia-ur
    Jobson, Daniel J.
    Woodell, Glenn A.
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2011, 22 (03) : 237 - 250
  • [46] Microscopic image contrast and brightness enhancement using multi-scale retinex and cuckoo search algorithm
    Biswas, Biswajit
    Roy, Pritha
    Choudhuri, Ritamshirsa
    Sen, Biplab Kanti
    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON ECO-FRIENDLY COMPUTING AND COMMUNICATION SYSTEMS, 2015, 70 : 348 - 354
  • [47] A Novel Color Image Fusion Method Based on the Multi-scale Retinex and DWT
    Zhang, Xiuqiong
    2009 INTERNATIONAL CONFERENCE ON INFORMATION MANAGEMENT AND ENGINEERING, PROCEEDINGS, 2009, : 395 - 398
  • [48] Video Image Dehazing Algorithm Based on Multi-scale Retinex with Color Restoration
    Mei Xue
    Yang Ji
    Zhang Yuyan
    Li Weiwei
    Zhang Jiugen
    2016 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2016), 2016, : 195 - 200
  • [49] A Medical Image Enhancement Method Based on Improved Multi-Scale Retinex Algorithm
    Qin, Yunchu
    Luo, Fugui
    Li, Mingzhen
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2020, 10 (01) : 152 - 157
  • [50] Multi-scale Retinex Image Enhancement Algorithm Based on Fabric Defect Database
    Wang, Huang
    Duan, Fajie
    Zhou, Weiti
    2019 INTERNATIONAL CONFERENCE ON OPTICAL INSTRUMENTS AND TECHNOLOGY: OPTOELECTRONIC IMAGING/SPECTROSCOPY AND SIGNAL PROCESSING TECHNOLOGY, 2020, 11438