重庆理工大学学报：自然科学2012，Vol.26Issue(8)：46-53,8.
一种基于高斯混合模型的红外图像自适应均衡和对比度增强算法
An Automatic Equalization and Contrast Enhancement Algorithm for Infrared Image Based on Gaussian Mixture Modeling
摘要
Abstract
The human eye is not sensitive to small variations around dense data but is more sensitive to widely scattered fluctuations. Thus, in order to dense data with low standard deviation should be ard deviation should be compacted. This retained. In order to achieve this, we use increase the contrast while retaining image details, dispersed, where as scattered data with high stand- operation should be the GMM to partiti done so that the gray-level distribution is on the distribution of the input image into a mixture of different Gaussian components, then transforming the algorithm according to the purpose of image enhancement关键词
自适应均衡/对比度增强/主导高斯成分/正态分布Key words
automatic equalization/contrast enhancement/dominant Gaussian component/normal distribution分类
信息技术与安全科学引用本文复制引用
陈小波,鲁新平,张升斌..一种基于高斯混合模型的红外图像自适应均衡和对比度增强算法[J].重庆理工大学学报：自然科学,2012,26(8):46-53,8.基金项目
“十二五”国防预研项目 （）
