液晶与显示Issue(2)：300-309,10.DOI:10.3788/YJYXS20153002.0300
高斯混合模型自适应微光图像增强
Automatic low light level image enhancement using Gaussian mixture modeling
摘要
Abstract
In order to improve the output quality of visible light sensor in low-light environment,an adaptive image enhancement algorithm using Gaussian mixture modeling is proposed in this paper. The histogram of image is modeled with Gaussian mixture modeling and the improved EM algorithm is used to fit the histogram and get the best parameters.Then,the histogram is separated into sub-his-tograms based on the intersections of Gaussian components.Finally,the mapping is achieved accord-ing to the parameters of output image,and the final enhanced image is obtained by the maximum en-tropy preserving method which tends to the characteristics of human visual.The experimental results show that the algorithm can determine the optimal number of clusters adaptively and improve the speed of the histogram fitting which costs 0.37 s averagely.Comparing with traditional methods,the enhancement result is superior in terms of objective evaluations of related information entropy and tex-ture information.It can improve the contrast of the low light level image and maintain the details.关键词
图像增强/直方图/高斯混合模型/微光图像Key words
image enhancement/histogram/Gaussian mixture model/low light level image分类
信息技术与安全科学引用本文复制引用
陈莹,朱明,刘剑,李兆泽..高斯混合模型自适应微光图像增强[J].液晶与显示,2015,(2):300-309,10.基金项目
国家自然科学基金(No．61203242) （No．61203242）
