基于YCbCr颜色空间的Retinex低照度图像增强方法研究

针对Retinex理论的低照度图像增强算法中光照图像估计问题,提出一种基于YCbCr颜色空间的低照度图像增强方法.该方法将原始低照度图像从RGB(Red Green Blue)颜色空间转换到YCbCr颜色空间,提取该空间中Y分量构建为原始光照图像分量L1(x,y),并对L1(x,y)进行Gamma校正得到增强的光照图像分量L2(x,y),经Retinex模型得到增强图像R(x,y),采用多尺度细节增强方法对图像R(x,y)进行细节增强,得到最终增强图像Re(x,y).实验结果表明,所提方法不仅能有效提升亮度,避免亮度和色彩失真,增强了图像的细节信息并获得了更好的视觉效果,而且运行速度快.

Low-light Image Enhancement Method Using Retinex Method Based on YCbCr Color Space

Aiming at the problem of illumination image estimation in low-light image enhancement algorithm of the Retinex model,a low-light image enhancement method based on YCbCr color space is proposed.The original low-light image is transformed from RGB(Red Green Blue)color space to YCbCr color space.The Y component in YCbCr color space is extracted and the initial illumination map L1(x,y)is constructed.The enhanced illumination image L2(x,y)is obtained by the gamma transformation of L1(x,y),the enhanced image R(x,y)is obtained according to the Retinex model,and we use a multi-scale approach to boost the details of the image R(x,y)and obtain the final enhanced image Re(x,y).The experimental results show that,the method can not only effectively improve the brightness of the low-light images,enhance the details of the image,obtain a better visual effect with fewer color and lightness distortions,but also has a faster running speed.