Image Cleaning and Enhancement Technique for Underwater Mining

被引:0
|
作者
Rajesh, Shravan Dev [2 ]
Almeida, Jose Miguel [1 ,2 ]
Martins, Alfredo [1 ,2 ]
机构
[1] INESC TEC INESC Technol & Sci, Porto, Portugal
[2] Polytech Inst Porto, ISEP Sch Engn, Porto, Portugal
来源
基金
欧盟地平线“2020”;
关键词
Image cleaning; Image processing; Image enhancement; Color correction; Computer vision; Underwater robots; Underwater mining;
D O I
10.1109/oceanse.2019.8866882
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
The exploration of water bodies from the sea to land filled water spaces has seen a continuous increase with new technologies such as robotics. Underwater images is one of the main sensor resources used but suffer from added problems due to the environment. Multiple methods and techniques have provided a way to correct the color, clear the poor quality and enhance the features. In this paper, we present the work of an Image Cleaning and Enhancement Technique which is based on performing color correction on images incorporated with Dark Channel Prior(DCP) and then taking the converted images and modifying them into the Long, Medium and Short(LMS) color space, as this space is the region in which the human eye perceives colour. This work is being developed at INESC TEC robotics and autonomous systems laboratory. Our objective is to improve the quality of images for and taken by robots with the particular emphasis on underwater flooded mines. The paper describes the architecture and the developed solution. A comparative analysis with state of the art methods and of our proposed solution is presented. Results from missions taken by the robot in operational mine scenarios are presented and discussed and allowing for the solution characterization and validation.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Underwater Image Enhancement using Deep Learning
    Naresh Kumar
    Juveria Manzar
    Shubham Shivani
    Multimedia Tools and Applications, 2023, 82 : 46789 - 46809
  • [42] Metalantis: A Comprehensive Underwater Image Enhancement Framework
    Wang, Hao
    Zhang, Weibo
    Bai, Lu
    Ren, Peng
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62 : 1 - 19
  • [43] Underwater Image Enhancement Using Adaptive Algorithms
    Luchman, Shaneer
    Viriri, Serestina
    PROGRESS IN ARTIFICIAL INTELLIGENCE AND PATTERN RECOGNITION, 2021, 13055 : 316 - 326
  • [44] DuGAN: An effective framework for underwater image enhancement
    Zhang, Huiqing
    Sun, Luyu
    Wu, Lifang
    Gu, Ke
    IET IMAGE PROCESSING, 2021, 15 (09) : 2010 - 2019
  • [45] Underwater image enhancement by dehazing and color correction
    Li, Chongyi
    Guo, Jichang
    JOURNAL OF ELECTRONIC IMAGING, 2015, 24 (03)
  • [46] Underwater Image Enhancement by Gaussian Curvature Filter
    Xiong, Jiaying
    Dai, Yuxiang
    Zhuang, Peixian
    2019 IEEE 4TH INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP 2019), 2019, : 1026 - 1030
  • [47] Underwater Image Enhancement with An Adaptive Dehazing Framework
    Qing, Chunmei
    Huang, Wenyou
    Zhu, Siqi
    Xu, Xiangmin
    2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2015, : 338 - 342
  • [48] An approach to underwater image enhancement based on image structural decomposition
    Ji Tingting
    Wang Guoyu
    JOURNAL OF OCEAN UNIVERSITY OF CHINA, 2015, 14 (02) : 255 - 260
  • [49] UIALN: Enhancement for Underwater Image With Artificial Light
    Li, Mengyao
    Wang, Kun
    Shen, Liquan
    Lin, Yufei
    Wang, Zhengyong
    Zhao, Qijie
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 33 (08) : 3622 - 3637
  • [50] Leveraging Deep Statistics for Underwater Image Enhancement
    Wang, Yang
    Cao, Yang
    Zhang, Jing
    Wu, Feng
    Zha, Zheng-Jun
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2021, 17 (03)