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王晗, 朴斗福, 魏明, 施佺. 信息熵-保真度联合度量函数的单幅图像去雾方法[J]. 计算机辅助设计与图形学学报, 2019, 31(7): 1175-1182. DOI: 10.3724/SP.J.1089.2019.17435
引用本文: 王晗, 朴斗福, 魏明, 施佺. 信息熵-保真度联合度量函数的单幅图像去雾方法[J]. 计算机辅助设计与图形学学报, 2019, 31(7): 1175-1182. DOI: 10.3724/SP.J.1089.2019.17435
Wang Han, Park Dubok, Wei Ming, Shi Quan. A Single Image Dehazing Method Based on Entropy-Information Fidelity Joint Measure Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(7): 1175-1182. DOI: 10.3724/SP.J.1089.2019.17435
Citation: Wang Han, Park Dubok, Wei Ming, Shi Quan. A Single Image Dehazing Method Based on Entropy-Information Fidelity Joint Measure Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(7): 1175-1182. DOI: 10.3724/SP.J.1089.2019.17435

信息熵-保真度联合度量函数的单幅图像去雾方法

A Single Image Dehazing Method Based on Entropy-Information Fidelity Joint Measure Function

  • 摘要: 为了增强雾霾图像对比度的同时有效地弥补颜色缺失,提出一种信息熵与保真度相结合的单幅图像去雾方法.首先利用四叉树分割的雾霾变换图像估计大气光线;然后构造信息熵与保真度的联合度量目标函数,估计局部图像块的大气透射率;再采用加权的最小二乘方法对大气透射率的初次估计值进行精细化处理;最后根据大气散射模型求解出去雾后的图像.采用多种室外场景下不同分辨率的真实雾霾图像作为测试数据,通过多组性能指标的比较分析;实验结果证明,该方法在增强图像对比度的同时有效地保留了图像色彩信息.

     

    Abstract: In order to enhance the image contrast and compensate the loss of color information simultane- ously, this paper proposes a novel single image dehazing method based on entropy and information fidelity. Firstly, the global atmospheric light is estimated by quad-tree form transformed hazy image. Then, transmis- sion is estimated by a joint objective function based on entropy and fidelity at non-overlapped sub-block re- gions. It is further refined by weighted least squares optimization to alleviate block artifacts. Finally, dehazed image is constructed from atmospheric scattering model. Real haze outdoor images under different scenes and resolutions are used as test data. Moreover, multiple evaluation indicators are employed to syn- thetically analyze the performance of proposed method. The comparison experiment results show that pro- posed approach performances better than other conventional methods in many evaluating indicators espe- cially in colorfulness and global contrast factor.

     

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