Single underwater image restoration by blue-green channels dehazing and red channel correction

Chongyi Li, Jichang Quo, Yanwei Pang, Shanji Chen, Jian Wang
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引用次数: 109

Abstract

Restoring underwater image from a single image is know to be ill-posed, and some assumptions made in previous methods are not suitable for many situations. In this paper, we propose a method based on blue-green channels dehazing and red channel correction for underwater image restoration. Firstly, blue-green channels are recovered via dehazing algorithm based on an extension and modification of Dark Channel Prior algorithm. Then, red channel is corrected following the Gray-World assumption theory. Finally, in order to resolve the problem which some recovered image regions may look too dim or too bright, an adaptive exposure map is built. Qualitative analysis demonstrates that our method significantly improves visibility and contrast, and reduces the effects of light absorption and scattering. For quantitative analysis, our results obtain best values in terms of entropy, local feature points and average gradient, which outperform three existing physical model available methods.
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采用蓝绿通道去雾和红通道校正的单幅水下图像恢复方法
从单幅图像恢复水下图像是一种病态的方法,以前的方法所做的一些假设并不适用于许多情况。本文提出了一种基于蓝绿通道去雾和红通道校正的水下图像恢复方法。首先,在暗通道先验算法的基础上进行扩展和改进,通过去雾算法恢复蓝绿通道;然后,根据灰色世界假设理论对红色通道进行校正。最后,为了解决某些恢复图像区域看起来太暗或太亮的问题,构建了自适应曝光图。定性分析表明,我们的方法显著提高了能见度和对比度,减少了光吸收和散射的影响。在定量分析方面,我们的结果在熵、局部特征点和平均梯度方面获得了最佳值,优于现有的三种物理模型可用方法。
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