基于YUV色彩空间的Retinex夜间图像增强算法

通常夜间拍摄图像容易出现细节分辨不清的情况。为了改善夜间拍摄图像的质量,提出一种基于YUV色彩空间的Retinex图像增强算法和色度自适应校正方法。首先将图像从RGB色彩空间转换到YUV色彩空间;其次对明亮度分量Y采用多尺度Retinex算法增强,并利用增强后的Y分量对色度分量U、V进行自适应校正;最后将图像转换到RGB色彩空间输出,使图像在细节信息得到增强的同时颜色得到较好的保持。通过与其他Retinex算法比较,实验结果表明该算法在颜色保持和细节增强方面能够达到很好的效果。

Night Image Enhancement Using Retinex Algorithm Based on YUV Color Space

In general, details of night images are easily blurred. In order to improve the quality of the night image, a new Retinex algorithm is proposed based on the YUV color space with chrominance components correction strategy. Firstly, the image is converted from RGB color space to YUV color space. Then the brightness component Y is enhanced by using multi-scale Retinex algorithm. At the same time, chrominance components U, V are corrected based on Y component after enhancement. Finally, the image is converted to RGB color space to output. Results show that while image details are enhanced the color has been maintained. By comparison with other Retinex algorithms, experimental results show that the algorithm applied to night image enhancement has achieved good results in image color fidelity and detail information enhancement respects.