Study of Relative Radiometric Normalization Based on Multitemporal ASTER Images
Both the reference image and original image are respectively decomposed into low-frequency components and high-frequency components by wavelet transform. Then, count the low-frequency components of the two images by margin calculation and select the PIF points to correct while the high-frequency components remain unchanged. Finally, reconstract the high-frequency components of discorrected original image and low-frequency components of corrected to get the corrected image. The method eliminates the radiation difference resulted from different time periods and save the radiation difference caused by the change of surface features themselves in the original image. The relative radiometric correction achieves a better effect, and can improve the accuracy of remote sensing dynamic monitoring.
Y. Xing et al., "Study of Relative Radiometric Normalization Based on Multitemporal ASTER Images", Advanced Materials Research, Vols. 108-111, pp. 190-194, 2010