An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
复制标题
水下成像图像增强和图像恢复方法的实验综述
DOI：
10.1109/access.2019.2932130
复制
发表时间：
2019-07
期刊：
影响因子：
3.9
通讯作者：
Antonio Liotta
中科院分区：
文献类型：
--
作者：
Yan Wang;Wei Song;Giancarlo Fortino;Antonio Liotta
水下图像在海洋探测中起着关键作用，但由于光在水介质中的吸收和散射，水下图像的质量往往会严重下降。虽然最近在图像增强和恢复的总体领域取得了重大突破，但还没有具体捕捉到提高水下图像质量的新方法的适用性。在本文中，我们回顾了针对典型的水下图像损伤的图像增强和恢复方法，包括一些极端的退化和失真。首先，根据水下成像模型(IFM)，介绍了导致水下图像质量下降的主要原因。然后，我们回顾了水下复原的方法，包括无IFM方法和基于IFM的方法。接下来，我们提出了一个基于实验的比较评估的最新技术的IFM-自由和基于IFM的方法，也考虑了基于IFM的方法的基于先验的参数估计算法，使用主观和客观的分析(使用的代码可在https://github.com/wangyanckxx/Single-Underwater-Image-Enhancement-and-Color-Restoration).免费获得从本文开始，我们找出了现有方法的主要缺陷，并对未来这一领域的研究提出了建议。我们对水下图像增强和恢复的回顾为研究人员提供了必要的背景，以了解这一重要领域的挑战和机遇。
Underwater images play a key role in ocean exploration but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major breakthroughs have been made recently in the general area of image enhancement and restoration, the applicability of new methods for improving the quality of underwater images has not specifically been captured. In this paper, we review the image enhancement and restoration methods that tackle typical underwater image impairments, including some extreme degradations and distortions. First, we introduce the key causes of quality reduction in underwater images, in terms of the underwater image formation model (IFM). Then, we review underwater restoration methods, considering both the IFM-free and the IFM-based approaches. Next, we present an experimental-based comparative evaluation of the state-of-the-art IFM-free and IFM-based methods, considering also the prior-based parameter estimation algorithms of the IFM-based methods, using both subjective and objective analyses (the used code is freely available at https://github.com/wangyanckxx/Single-Underwater-Image-Enhancement-and-Color-Restoration). Starting from this paper, we pinpoint the key shortcomings of existing methods, drawing recommendations for future research in this area. Our review of underwater image enhancement and restoration provides researchers with the necessary background to appreciate challenges and opportunities in this important field.
登录
查看更多内容
影响因子：
10.6
作者：
Wang, Shuhang;Zheng, Jin;Li, Bo
通讯作者：
Li, Bo
基于DSNMF的水下图像色彩恒常性
影响因子：
2.3
作者：
Liu Xiaopeng;Zhong Guoqiang;Liu Cong;Dong Junyu
通讯作者：
Dong Junyu
DOI：
10.1109/icit.2017.7915500
发表时间：
2017-03
期刊：
2017 IEEE International Conference on Industrial Technology (ICIT)
影响因子：
--
作者：
Yafei Wang;Xueyan Ding;Ruoqian Wang;Jun Zhang;Xianping Fu
通讯作者：
Yafei Wang;Xueyan Ding;Ruoqian Wang;Jun Zhang;Xianping Fu
DOI：
10.1007/11585978_5
发表时间：
2005-11
期刊：
--
影响因子：
--
作者：
L. Torres-Méndez;G. Dudek
通讯作者：
L. Torres-Méndez;G. Dudek
DOI：
10.1109/cvprw.2018.00162
发表时间：
2018-06
期刊：
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
影响因子：
--
作者：
Patricia L. Suárez;A. Sappa;B. Vintimilla;R. Hammoud
通讯作者：
Patricia L. Suárez;A. Sappa;B. Vintimilla;R. Hammoud