徐兴贵, 杨平, 刘永利. 基于全尺度Retinex算法的夜间图像去雾[J]. 微电子学与计算机, 2017, 34(7): 132-136.
引用本文: 徐兴贵, 杨平, 刘永利. 基于全尺度Retinex算法的夜间图像去雾[J]. 微电子学与计算机, 2017, 34(7): 132-136.
XU Xing-gui, YANG Ping, LIU Yong-li. Night Image Dehazing Based on Full-scale Retinex Algorithm[J]. Microelectronics & Computer, 2017, 34(7): 132-136.
Citation: XU Xing-gui, YANG Ping, LIU Yong-li. Night Image Dehazing Based on Full-scale Retinex Algorithm[J]. Microelectronics & Computer, 2017, 34(7): 132-136.

基于全尺度Retinex算法的夜间图像去雾

Night Image Dehazing Based on Full-scale Retinex Algorithm

  • 摘要: 提出了一种基于全尺度Retinex算法的夜间图像去雾处理模型.首先由暗原色先验理论估计图像的全局透射率, 接着将透射率估计值映射为全尺度的环绕函数进而求取照度分量, 最后基于Retinex原理进行去雾处理.实验结果表明, 该方法能够有效地处理各种夜间非均匀照明条件下的有雾图, 同时还能获得图像的全尺度透射率图信息.

     

    Abstract: In this psper a novel nighttime image dehazing model based on the full-scale Retinex algorithm is proposed. We firstly estimate the global transmissivity of the image based on the dark prior theory. Then the estimated transmissivity values are mapped to the full-scale surround functions to get the illumination component. Finally, Retinex principle is used to dehaze. This method can be used to deal with various nighttime under foggy and inhomogeneous illumination conditions effectively, and to get full-scale transmissivity of the image.

     

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