Jun Liu , Xing Wang , Min Chen , Shuguang Liu , Zhenfeng Shao , Xiran Zhou and Ping Liu
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; E-Mails: liujun@cigit.ac.cn (J.L.); liushuguang@cigit.ac.cn (S.L.)
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; E-Mail: dongbei20055@163.com
State key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China; E-Mails: chenminzs@163.com (M.C.); zhouxiranjuven@163.com (X.Z.)
China Laboratory for High Performance Geo-computation, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; E-Mail: liupingpp@gmail.com
Abstract Building a mathematical model of uneven illumination and contrast is difficult, even impossible. This paper presents a novel image balancing method for a satellite image. The method adjusts the mean and standard deviation of a neighborhood at each pixel and consists of three steps, namely, elimination of coarse light background, image balancing, and max-mean-min radiation correction. First, the light background is roughly eliminated in the frequency domain. Then, two balancing factors and linear transformation are used to adaptively adjust the local mean and standard deviation of each pixel. The balanced image is obtained by using a color preserving factor after max-mean-min radiation correction. Experimental results from visual and objective aspects based on images with varying unevenness of illumination and contrast indicate that the proposed method can eliminate uneven illumination and contrast more effectively than traditional image enhancement methods, and provide high qualityimages with better visual performance. In addition, the proposed method not only restores color information, but also retains image details.
