Color Calibration of Remote Sensing Imagery Based on Orthogonal Space Transformation

Abstract

Due to different atmospheric conditions, seasonal changes in vegetation characteristics and other reasons, the remote sensing images captured at different time may be quite different in color, brightness and so on. In this paper, coupled with statistics classification, three common orthogonal space transformations were used to calibrate the color difference respectively. Compared with conventional methods such as the overlapping region correction and histogram matching, the results show that orthogonal transform could achieve better correction effects. The lαβ transform gets the best corrected result among three orthogonal space transform methods.