基于YUV 颜色空间的图像去雾算法

针对有雾天气条件下, 获得的图像严重降质问题, 提出一种基于YUV 颜色空间的快速图像去雾算法。该算法以大气散射模型为基础, 利用YUV 颜色模型提取出有雾图像的亮度分量, 对此亮度分量图像进行高斯滤波后得到散射光; 求出有雾图像的最大亮度值作为大气光, 进而求得清晰的无雾图像。实验结果表明, 该算法不仅有效地提高了降质图像的质量, 而且处理速度快, 能很好地保持图像的细节。

Single Image Dehazing Based on YUV Color Space

In the foggy condition captured image is seriously degraded, we propose a fast image defogging algorithm based on YUV color space. Based on atmospheric scattering model, firstly the luminance is extracted, geting the scattering light after Gauss filter; then the maximum brightness value of the image as the atmospheric airlight; then can obtain a clear image. The experimental results show that the algorithm effectively improves the image quality, and can keep good image details.