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摘要: 针对暗通道先验算法最小滤波使用的不足，提出一种基于高斯权重衰减的迭代优化去雾方法.该方法首先利用Kirsch算子滤波构造高斯函数逼近暗通道操作，然后用交叉双边滤波消除纹理效应，其次，在透射率为最优的前提下，利用高斯暗通道来简化大气散射模型，从而得到粗略透射率；为了得到最优透射率，使用Kirsch和Laplacian算子构成的一组高阶滤波器进行迭代处理，从而获得最优效果；最后，结合大气散射模型复原无雾图像.通过大量实验测试验证，所提假设成立，复原的图像细节明显，明亮度适宜，并且在客观评价中也体现出了优势.Abstract: Aiming at the shortcoming of the minimum filtering of dark channel prior algorithm, an iterative optimization defogging algorithm using the Gaussian weight decay is proposed. This method uses the Kirsch operator to construct a Gaussian function to approximate the dark channel operation and eliminate the texture effect by cross-bilateral filters. Secondly, under the optimal transmission, the proposed Gaussian dark channel is used to simplify the atmospheric scattering model to result in a rough transmission. In order to obtain the optimal transmission, a set of high-order filters composed of Kirsch and Laplacian operators are used to iterate towards the optimal effect. Finally, the atmospheric scattering model is used to recover the haze free image. Through a large number of experimental tests it is verified that the proposed hypothesis is valid and restoration of image details is obvious, bright and appropriate. Moreover, it also performs well in the objective evaluation.
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Key words:
- Gaussian attenuation /
- dehaze /
- iterative optimization /
- atmospheric scattering model
1) 本文责任编委 左旺孟 -
图 3 无雾图像高斯暗通道灰度级分布
Fig. 3 Gaussian dark channel grayscale distribution of dehazed images
图 5 高阶滤波器组(中心为Laplacian算子, 周围为Kirsch算子)
Fig. 5 High order filter bank (Laplacian center, Kirsch operator around)
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