Relative radiometric normalization of multi temporal remote sensing images is the prerequisite of dynamic monitoring of remote sensing. The effect of pseudo-invariant feature(PIF) relative radiation correction is largely determined by the selection of PIF points. The method of ordinary artificial point selection has a lot of shortcomings, such as strong subjectivity and the fact that the points' quality and quantity cannot be controlled. The following operations proposed in this paper will solve these problems. First, the accurate geometric correction and registration of the two TM images were carried out. Then the PIF was refined in stepwise way by combining the band ratio operation and quality control to improve the quality of PIF and reduce the subjectivity of its selection. The quality of selected points was evaluated by using the correlation coefficient of corresponding sample points of each band. The method of least square regression analysis was used to get the gain and offset based on the qualified PIF points selected. Then the relative radiometric correction of the two TM images was carried out. The spectrum curves of typical features, root mean square error, NDVI statistics between corrected image and original image were analyzed. The results show that the correction effect is satisfactory.
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2017, Vol. 29 
