Improved relative radiometric normalization method of remote sensing images for change detection

摘要: Relative radiometric normalization (RRN) of remotely sensed images is often a preprocessing step during time series analysis and change detection. Conventional RRN methods may lessen the radiation difference changed pixels in process, thus reducing accuracy To solve this problem, we propose relative correction method based on wavelet transform iteratively reweighted multivariate alteration detection (IR-MAD). A applied to separate high low frequency components both target image reference image. The remain unprocessed preserve information. We use IR-MAD algorithm normalize component reverse reconstructs radiometrically normalized tested proposed with traditional histogram matching, mean variance, original method, combining low-pass filtering, was conducted evaluate quality. experiments show that can not only effectively eliminate overall between but also enable higher