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 quality images with better visual performance. In addition, the proposed method not only restores color information, but also retains image details.
This is an open access article distributed under the
Creative Commons Attribution License which permits unrestricted use, distribution,
and reproduction in any medium, provided the original work is properly cited.
Export to BibTeX
MDPI and ACS Style
Liu, J.; Wang, X.; Chen, M.; Liu, S.; Shao, Z.; Zhou, X.; Liu, P. Illumination and Contrast Balancing for Remote Sensing Images. Remote Sens. 2014, 6, 1102-1123.
Liu J, Wang X, Chen M, Liu S, Shao Z, Zhou X, Liu P. Illumination and Contrast Balancing for Remote Sensing Images. Remote Sensing. 2014; 6(2):1102-1123.
Liu, Jun; Wang, Xing; Chen, Min; Liu, Shuguang; Shao, Zhenfeng; Zhou, Xiran; Liu, Ping. 2014. "Illumination and Contrast Balancing for Remote Sensing Images." Remote Sens. 6, no. 2: 1102-1123.