改进的带色彩恢复的多尺度Retinex雾天图像增强算法

Improved enhancement algorithm of fog image based on multi-scale Retinex with color restoration

针对带色彩恢复的多尺度Retinex(MSRCR)算法不能有效地去除远景处的雾及灰度假设所带来的灰化问题提出了一种新的方法。新的方法对原雾天图像及其取反图像分别进行MSRCR算法处理;然后对处理后的取反图像再进行取反操作并和直接进行MSRCR算法处理的图像进行线性加权叠加;同时在MSRCR处理过程中把提取出来的反射分量与像素的原始亮度进行线性叠加,并计算均值和方差来自适应决定对比度的拉伸程度;最后统一拉伸到显示设备。实验结果表明,所提算法能取得较好的去雾效果,处理后的图像的标准差、平均亮度、信息熵、平方梯度等评价值均比原算法有所提高。所提算法方法简单、易于实现,对于实时视频去雾具有一定的意义。

An improved method for Multi-Scale Retinex with Color Restoration （MSRCR） algorithm was proposed, to remove the fog at the far prospect and solve gray hypothesis problem. First, original fog image was inverted. Then, MSRCR algorithm was used on it. The inverted image was to be inverted again and then was linearly superposed with the result which was processed by MSRCR algorithm directly . At the same time , the reflection component which was got during the process of the extraction was linearly superposed with the original luminance, and the mean and variance were calculated to decide the contrast stretching degree adaptively, finally, it was uniformly stretched to the display device. The experimental results show that the proposed algorithm can get a better effect of removing the fog. Evaluation values of the processed image, including standard difference, average brightness, information entropy, and squared gradient, are improved than the original algorithm. It is easy to implement and has important significance for real-time video to remove fog.