Study on Relative Radiometric Calibration of Multi–temporal High Resolution Remote Sensing Image

摘要

In this paper, a relative radiometric calibration method of multi-temporal high-resolution remote sensing images is proposed. Primary component analysis and correlation coefficients are used to get Pseudo-Invariant Features (PIFs). Firstly, Primary component analysis is taken to make difference images and threshold iteration is used to get optimal threshold according to correlation coefficient and numbers of PIFs. Then, least square regression analysis algorithm is taken to obtain the linear parameters between multi-temporal remote sensing images. Then, relative radiometric calibration is completed by estimated linear parameter. Experimental results, obtained on two sets of multi-temporal high-resolution remote sensing images, prove the effectiveness and robustness of the proposed approach compared to each threshold selection algorithm.