针对低照度环境下具有动态性的彩色图像辨识度相对较差的问题, 提出了基于人类视觉感知模型的对比度分辨率补偿算法。首先, 将图像从RGB空间转换到HSV空间, 保持H分量不变; 对V分量提取图像特征参数, 然后对V分量进行对比度分辨率补偿, 增强图像亮度; 并对S分量进行线性拉伸, 复原图像色彩信息; 最后将处理后的V分量和S分量与H分量进行反变换生成RGB空间新图像。实验结果表明, 该算法对低照度下具有动态性的彩色图像增强效果较好, 较好地保持了图像的细节, 取得了良好的视觉效果。

It is relatively difficult to identify the dynamic color images under low-light level. Therefore, in this paper, put forward is a kind of contrast resolution compensation algorithm based on human visual perception model. Firstly, a color image is transformed from RGB space into HSV space, the H elements remain unchanged. Secondly, it is to extract image feature parameters of the V element, then using contrast resolution compensate V elements so as to enhance the image brightness. Thirdly, the S element is linearly stretched to recover the color information of the images. Finally, the treated V elements, treated S elements and untreated H elements are used to construct a new enhanced image with RGB space by inverse transform. Experimental results show that the compensation method can enhance images and improve image quality.