Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior

Zuyun Jiang, Xiangdong Sun, Xiaochun Wang
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引用次数: 7

Abstract

Abstract Based on image segmentation and the dark channel prior, this paper proposes a fog removal algorithm in the HSI color space. Usually, the dark channel prior based defogging methods easily produce color distortion and halo effect when applied on images with a large sky area, because the sky region does not meet the prior assumption. For this reason, our method presents a new threshold sky region segmentation algorithm using the initial transmission map of the intensity component I. Based on the segmentation result, the initial transmission map is modified in turn, and finally refined by the guided filter. The saturation components S is reconstructed using the low frequencies of the V-transform to reduce noise, and stretched by multiplying a constant related to the initial transmission map. Experimental results show that the proposed algorithm has low time complexity and compelling fog removal result in both visual effect and quantitative measurement.
基于天空区域分割和暗通道先验的图像去雾算法
摘要提出了一种基于图像分割和暗通道先验的HSI色彩空间去雾算法。通常,基于暗通道先验的去雾方法在应用于天空面积较大的图像时,由于天空区域不满足先验假设,容易产生色彩失真和光晕效应。为此,我们的方法提出了一种新的阈值天空区域分割算法,利用强度分量i的初始透射图,根据分割结果对初始透射图进行依次修改,最后通过引导滤波进行细化。利用v变换的低频重构饱和分量S以降低噪声,并通过乘以与初始传输图相关的常数进行拉伸。实验结果表明,该算法具有较低的时间复杂度和较好的去雾效果。
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