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王多超, 王永国, 董雪梅, 胡晰远, 彭思龙. 贝叶斯框架下的单幅图像去雾算法[J]. 计算机辅助设计与图形学学报, 2010, 22(10): 1756-1761.
引用本文: 王多超, 王永国, 董雪梅, 胡晰远, 彭思龙. 贝叶斯框架下的单幅图像去雾算法[J]. 计算机辅助设计与图形学学报, 2010, 22(10): 1756-1761.
Wang Duochao, Wang Yongguo, Dong Xuemei, Hu Xiyuan, Peng Silong. Single Image Dehazing Based on Bayesian Framework[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(10): 1756-1761.
Citation: Wang Duochao, Wang Yongguo, Dong Xuemei, Hu Xiyuan, Peng Silong. Single Image Dehazing Based on Bayesian Framework[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(10): 1756-1761.

贝叶斯框架下的单幅图像去雾算法

Single Image Dehazing Based on Bayesian Framework

  • 摘要: 在有雾天气条件下拍摄的图像,由于光线在传播过程中受到空气中悬浮颗粒的散射,导致图像内容模糊不清,颜色偏灰白色.为了恢复出清晰的图像,根据大气散射物理模型,利用图像的稀疏先验知识,在贝叶斯框架下提出一种单幅图像去雾算法.该算法用图像梯度稀疏性先验来约束优化结果,并认为图像成像噪声服从零均值的高斯分布,然后用IRLS方法对其求解.实验结果表明,该算法能够很好地恢复图像的对比度和保持图像的真实颜色,噪声小,便于应用.

     

    Abstract: Because of light scattered by the suspended particles in the atmosphere,photographs taken in the foggy day look gray and are lack of visibility.In order to unveil the clear image's structures and colors,we propose a new algorithm based on the atmosphere scattering model using a single image and the image sparsity prior in Bayesian framework.The fog removal result is optimized under the constraint of the prior of the image gradient sparsity and the noise in the foggy image being the normal distribution with zero mean,and then the optimization function is computed using the IRLS algorithm.In our experiments,the algorithm has a good effect on restoring the clear image's contents and preserving the image's true colors.The noise in the output image is very weak that has advantage for many applications.

     

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