一种基于颜色恒常性的低照度图像增强方法

目的在彩色图像采集过程中,光源偏暗或曝光不足等因素常导致图像亮度和对比度偏低。提出一种基于颜色恒常性的低照度图像增强方法。方法利用HSV颜色空间消除颜色分量之间的相关性。保持色调分量不变,避免颜色失真;一方面使用改进后的MSR(多尺度Retinex)算法对亮度分量进行增强,提高图像的亮度和对比度;另一方面对饱和度分量进行自适应非线性拉伸以提高颜色的饱和度。结果提出的方法能够有效提高图像的对比度和信息熵,获得较好的视觉效果;将文中方法同传统MSR算法和MSRCR算法进行对比,文中方法各项客观评价指标均优于其他2种算法,并且具有更快的运行速度。结论文中方法能够快速有效地提高低照度图像的亮度和对比度,并且具有较强的颜色保真和细节再现能力,实验结果证明了文中方法的有效性。

Color Constancy-based Image Enhancement Method under Poor Illumination

The work aims to propose a color constancy-based image enhancement method under poor illumination regarding the low image brightness and contrast caused by such factors as poor illumination or underexposure in the process of color image acquisition. The HSV color space was used to eliminate the correlation between the color components and the hue component remained unchanged to avoid color distortion. On the one hand, the luminance component was enhanced with the improved MSR (Multi-scale Retinex) algorithm to strengthen the brightness and contrast of the image. On the other hand, the saturation component was subject to adaptive nonlinear stretching to improve color saturation. The proposed method could efficiently improve the contrast and information entropy of the image, and achieve better visual effects. Compare with the traditional MSR and MSRCR algorithms, the objective evaluation indicators of the proposed method were better, and the proposed method was much faster. The proposed method can efficiently improve the brightness and contrast of the image under poor illumination, and has a stronger ability to maintain color and reproduce image details. Experimental results demonstrate the effectiveness of the proposed method.