水下
人工智能
计算机视觉
计算机科学
颜色校正
色空间
色彩平衡
薄雾
颜色恒定性
色调
彩色图像
假彩色
频道(广播)
图像复原
失真(音乐)
图像融合
图像处理
图像(数学)
物理
地质学
计算机网络
放大器
海洋学
带宽(计算)
气象学
作者
Yiming Li,Zhu Chen,Junxin Peng,Liheng Bian
出处
期刊:Optics Express
[The Optical Society]
日期:2022-08-31
卷期号:30 (19): 33826-33826
被引量:6
摘要
Underwater imaging is usually affected by water scattering and absorption, resulting in image blur and color distortion. In order to achieve color correction and dehazing for different underwater scenes, in this paper we report a fusion-based underwater image enhancement technique. First, statistics of the hue channel of underwater images are used to divide the underwater images into two categories: color-distorted images and non-distorted images. Then, category-specific combinations of color compensation and color constancy algorithms are used to remove the color shift. Second, a ground-dehazing algorithm using haze-line prior is employed to remove the haze in the underwater image. Finally, a channel-wise fusion method based on the CIE L* a* b* color space is used to fuse the color-corrected image and dehazed image. For experimental validation, we built a setup to acquire underwater images. The experimental results validate that the category-specific color correction strategy is robust to different categories of underwater images and the fusion strategy simultaneously removes haze and corrects color casts. The quantitative metrics on the UIEBD and EUVP datasets validate its state-of-the-art performance.
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