人工智能
计算机视觉
计算机科学
失真(音乐)
图像复原
对比度(视觉)
光散射
一般化
图像(数学)
频道(广播)
光学
颜色校正
色彩平衡
彩色图像
数学
散射
图像处理
物理
放大器
数学分析
带宽(计算)
计算机网络
作者
Yan-Tsung Peng,Keming Cao,Pamela C. Cosman
标识
DOI:10.1109/tip.2018.2813092
摘要
Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media. In order to enhance and restore such images, we first estimate ambient light using the depth-dependent color change. Then, via calculating the difference between the observed intensity and the ambient light, which we call the scene ambient light differential, scene transmission can be estimated. Additionally, adaptive color correction is incorporated into the image formation model (IFM) for removing color casts while restoring contrast. Experimental results on various degraded images demonstrate the new method outperforms other IFM-based methods subjectively and objectively. Our approach can be interpreted as a generalization of the common dark channel prior (DCP) approach to image restoration, and our method reduces to several DCP variants for different special cases of ambient lighting and turbid medium conditions.
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