一种实用的可见光图像自适应对比度增强方法

提出了一种基于图像一阶、二阶统计特性的自适应可见光图像对比度增强方法。通过分析可见光图像数字特性,提取了图像序列两个时间平稳的特征,即均值和方差。以此为基础,在灰度域对图像进行对比度增强。实验结果表明,提出的方法有效地增强了图像的对比度,同时抑制了部分起伏的背景。该算法在视觉质量上优于传统的基于图像最大最小值的对比度增强方法和直方图均衡方法,而且易于实现。

A Practical Adaptive Contrast Enhancement Method of the Visible Image

Based on the first and the second order of image statistics characteristics, the adaptive visible image contrast enhancement method is presented. According to the analysis of the visible images statistics characteristics, It can obtain the two time-domain stabilizing characteristics, the mean and the standard deviation of image sequences, and based on them, image contrast is enhanced in gray-level domain. Results show that the method effectively improves image contrast and restrains some background clutter. In visual quality, the method is better than the contrast enhancement based on minimum and maximum of image gray-level and histogram equalization method. And the method can be realized very easily.