基于局部自适应伽马校正低照度图像增强  

Low-light Image Enhancement Based on Adaptive Local Gamma Correction

作　　者：张美的 余顺园 ZHANG Mei-di;YU Shun-yuan(College of Electronics and Information Engineering,Ankang University,Ankang 725000,China)

机构地区：[1]安康学院电子与信息工程学院,陕西安康725000

出　　处：《计算机与现代化》2023年第8期74-78,118,共6页Computer and Modernization

基　　金：国家自然科学青年基金资助项目(61801005)。

摘　　要：针对照度不均匀的图像,本文设计一种自适应局部伽马校正低照度图像增强方法。先统计局部邻域内像素的亮度特性,计算亮度的概率密度分布函数,根据图像局部场景内容对概率密度函数进行修正,将修正概率密度函数作为伽马校正系数计算依据,得到能随局部场景亮度自适应调整的伽马系数,实现基于自适应伽马校正低照度图像增强;随后通过修正色调和色彩饱和度,改善低照度图像增强过程中的色偏问题。本文方法使用简单,无需手动调整参数即可适应不同场景的低照度图像增强。实验结果表明本文方法能提高低照度彩色图像的亮度和局部反差,在获得更高对比度同时,能有效突出暗区的细节,无过曝和欠曝的现象出现,增强后的图像能呈现较好的色彩丰富度和自然度。For images with uneven illumination,an adaptive local Gamma correction method for low-illumination image enhance‐ment is designed.The algorithm uses the modified probability density function of the local area as the calculation basis of the Gamma correction coefficient,and adjusts the Gamma coefficient adaptively according to the content of the local scene of the im‐age.Meanwhile,by correcting the hue and color saturation,the color deviation problem in the process of low illumination image enhancement can be improved.The idea of the whole algorithm is simple,and it can adapt to the image enhancement of different scenes without manually adjusting the parameters.The experimental results show that the method in this paper can improve the brightness and local contrast of low-illumination color images,and at the same time obtain higher contrast,it can effectively highlight the details of dark areas,without the phenomenon of overexposure and underexposure,and the enhanced image can present better color richness and naturalness.

关 键 词：局部伽马校正 自适应 低照度图像 图像增强 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]