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高银, 云利军, 石俊生, 丁慧梅. 基于各向异性高斯滤波的暗原色理论雾天彩色图像增强算法[J]. 计算机辅助设计与图形学学报, 2015, 27(9): 1701-1706.
引用本文: 高银, 云利军, 石俊生, 丁慧梅. 基于各向异性高斯滤波的暗原色理论雾天彩色图像增强算法[J]. 计算机辅助设计与图形学学报, 2015, 27(9): 1701-1706.
Gao Yin, Yun Lijun, Shi Junsheng, Ding Huimei. Enhancement Dark Channel Algorithm of Color Fog Image Based on the Anisotropic Gaussian Filtering[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(9): 1701-1706.
Citation: Gao Yin, Yun Lijun, Shi Junsheng, Ding Huimei. Enhancement Dark Channel Algorithm of Color Fog Image Based on the Anisotropic Gaussian Filtering[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(9): 1701-1706.

基于各向异性高斯滤波的暗原色理论雾天彩色图像增强算法

Enhancement Dark Channel Algorithm of Color Fog Image Based on the Anisotropic Gaussian Filtering

  • 摘要: 针对经典的暗原色理论算法在处理雾天图像时色调和亮度失真问题,提出基于各向异性高斯滤波的暗原色理论雾天彩色图像增强算法.首先通过容差机制对图像区域进行分割,根据阈值判断明亮和非明亮区域;然后引入各向异性高斯滤波,对透射率图像进行保边平滑处理;最后再一次引入容差机制,实现对透射率图像的再次修正,得到准确透射率图像,进而获得无雾的图像.主观观察和客观评价结果表明,在整体和细节方面,该算法比经典的暗原色算法有更好的处理效果.

     

    Abstract: To deal with the image hue and brightness distortion problems in the classic dark channel theory algorithm, enhancement dark channel algorithm of color fog image based on the anisotropic Gaussian filtering is proposed. Firstly, the image was segmented by the tolerance mechanism and distinguished between bright areas and dark channel areas according to the threshold. Then, the edges of the transmission image were preserved and the others were smoothed by the anisotropic Gaussian filtering. At last, the obtained image was modified to get the accurate transmission image by the tolerance mechanism in order to get a defogging image. Through the subjective observation and objective evaluation, the algorithm is better than the classic dark channel algorithm in the overall and details.

     

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