结合天空分割和超像素级暗通道的图像去雾算法

doi:10.13229/j.cnki.jdxbgxb20180208

摘要/Abstract

摘要：

为了提升去雾图像质量，提出了一种基于天空分割和超像素级暗通道的单幅图像去雾方法。首先提出一种简单有效的多阈值天空分割方法，可将图像划分为天空区域和非天空区域；其次，根据天空区域估计大气光值；然后分别估计两类区域的透射率，对天空区域利用该区域无雾和有雾时暗通道值间的线性关系直接估计其透射率，对非天空区域则通过计算超像素级暗通道值来估计透射率；最后根据大气散射模型恢复无雾图像。实验结果表明，与现有方法相比，本文方法能更准确地分割天空且阈值自适应性强，大气光和透射率估计也更准确高效。采用本文方法得到的去雾图像具有对比度高、颜色自然、细节清晰等优点。

关键词: 信息处理技术, 图像去雾, 透射率, 暗通道先验, 超像素

Abstract:

In order to improve the quality of restored images, a single image dehazing approach based on sky segmentation and superpixel-level dark channel model is proposed. First, a simple but effective multi-threshold sky segmentation method is presented, which divides the image into sky area and non-sky area. Second, the atmospheric light is estimated in sky area. Third, the transmission maps of the two types of areas are estimated respectively. For sky area, the transmission is directly estimated by the linear relationship between the dark channel values of clear images and the corresponding hazy images. For non-sky area, the transmission is estimated by superpixel-level dark channel values. Finally, the haze-free image can be restored by the atmospheric scattering model. Experimental results show that, compared with the existing methods, the proposed method can segment the sky more accurately with better adaption of the thresholds, and can estimate the atmospheric light and the transmission map with higher accuracy and efficiency. Moreover, the dehazed images obtained by the proposed method have many advantages such as high contrast, natural color and abundant details.

Key words: information processing technology, image dehazing, transmission, dark channel prior, super?pixel

中图分类号:

TN919.8

王柯俨,胡妍,王怀,李云松. 结合天空分割和超像素级暗通道的图像去雾算法[J]. 吉林大学学报(工学版), 2019, 49(4): 1377-1384.

Ke⁃yan WANG,Yan HU,Huai WANG,Yun⁃song LI. Image dehazing algorithm by sky segmentation and superpixel⁃level dark channel[J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1377-1384.

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