摘要
为了提高可变光照条件下的人脸图像整体效果,提出一种基于改进单尺度Retinex的光照变化人脸增强算法。首先对人脸图像进行对数变换,经过曲波变换得到高频和低频两部分;然后采用双边滤波对高频进行去噪处理,同时采用Kimmel变分模型对低频部分进行光滑滤波;最后对人脸图像进行重构,并对图像进行伽马校正处理。
In order to improve the overall effect of face images with variable illumination,this paper proposed a novel face enhancement algorithm with variable illumination based on single scale Retinex.Firstly,the face images are logarithmically transformed,and the image is transformed into frequency and low frequency part by curvelet transform.Secondly,the bilateral filtering is used to denoise the high frequency while Kimmel variation model is used to smooth filtering low frequency part.Finally,the image is reconstructed,and Gamma is used to correct the image.The experimental results on Yale B database show that the proposed algorithm can prevent the＂halos＂phenomenon,and can restore the original face image,so the face image is more suitable for human eye observation.
出处
《中国科学基金》
CSSCI
CSCD
北大核心
2016年第2期105-105,共1页
Bulletin of National Natural Science Foundation of China
基金
国家自然科学基金（61272297）
江苏师范大学自然科学基金（13XLB03）资助
