《现代计算机技术与应用》最新文章推荐---《多尺度Retinex算法在不同彩色空间图像去雾效果评估》

摘要：由于近年来雾霾频发，对于室外图像的采集造成一定困扰。图像去雾成为新的热点话题。本文针对图像去雾，首先研究了 Retinex 算法，并介绍了图像处理中常用的 RGB、HSV、RGB、YCbCr 这 4 种颜色空间。对 HSV、RGB、YCbCr 这 3 种颜色图像只进行亮度分量去雾，加快了速度。同时给出了信息熵（Entropy）、对比度（Contrast）、平均亮度 (Luminance)、平均梯度 (Gradient)4个指标对去雾后的图像进行评价。最后得出结论，Retinex 算法在 YCbCr 颜色空间中去雾的效果最佳。

Due to the frequent occurrence of haze in recent years, the collection ofoutdoor images has caused some problems. Image defogging has become a newhot topic. First, Retinex algorithm is studied for fog removal, and four color Spacescommonly used in image processing, including RGB, HSV, RGB and YCbCr, areintroduced. HSV, RGB, YCbCr color images are only used for brightness componentdefogging, which picks up the speed. Then, Information Entropy, Contrast, averageLuminance and average Gradient that the four indicators are given to evaluate imageafter fog removal. Finally, Retinex algorithm has the best effect to remove fog in YCbCrcolor space.

作者：崔倩倩  李瑞洋