Inland waterway image haze-removal based on the dark-channel prior

W. Liu, Xianqiao Chen, X. Chu
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Abstract

Dark-channel prior is a perfect theory to restore the outdoor haze image, but the color distortion is emerged when processing the bright region such as sky. Especially for inland river haze image, there is a large area of sky in image. To solve this problem, an improved dehazing algorithm is proposed in this paper. It first segments the haze image into sky and non-sky region through image segmentation algorithm, and then the dark-channel prior is used to deal with two regions to obtain the adaptive estimation of the transmission rate respectively. Finally, two transmission rates are combined to restore the inland river haze image. Experimental results show that the proposed algorithm provides significant advantage in producing more natural sky region, while achieving the image restoration of the non-sky region in inland river haze image.
基于暗通道先验的内河航道图像去雾
暗通道先验是恢复室外雾霾图像的理想理论,但在处理天空等明亮区域时,会产生色彩失真。特别是对于内陆河雾霾图像,图像中有大面积的天空。为了解决这一问题,本文提出了一种改进的除雾算法。首先通过图像分割算法将雾霾图像分割为天空和非天空区域,然后利用暗信道先验对两个区域分别进行处理,得到传输速率的自适应估计。最后,结合两种传输速率恢复内陆河雾霾图像。实验结果表明,该算法在产生更自然的天空区域方面具有显著优势,同时实现了内陆河雾霾图像中非天空区域的图像恢复。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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