光子学报, 2020, 49 (2): 0210002, 网络出版: 2020-03-19
基于YCbCr颜色空间的Retinex低照度图像增强方法研究 下载: 764次
Low-light Image Enhancement Method Using Retinex Method Based on YCbCr Color Space
Retinex模型 图像增强 光照估计 Gamma校正 细节增强 Retinex model Image enhancement Illumination estimation Gamma correction Detail boosting
摘要
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L 1(x,y),并对L 1(x,y)进行Gamma校正得到增强的光照图像分量L 2(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R e(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.
Abstract
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 L 1(x, y) is constructed. The enhanced illumination image L 2(x, y) is obtained by the gamma transformation of L 1(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 R e(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.
田会娟, 蔡敏鹏, 关涛, 胡阳. 基于YCbCr颜色空间的Retinex低照度图像增强方法研究[J]. 光子学报, 2020, 49(2): 0210002. Hui-juan TIAN, Min-peng CAI, Tao GUAN, Yang HU. Low-light Image Enhancement Method Using Retinex Method Based on YCbCr Color Space[J]. ACTA PHOTONICA SINICA, 2020, 49(2): 0210002.