Keywords: 
• remote sensing /
• hyperspectral images /
• registration /
• Gaussian fitting

Abstract: The traditional registration method is based on the search area registration and it is carried out at control points of the image coordinates of discrete points, but this method will limit the positioning accuracy of the registration control point. Aiming at this problem, a high spectral registration method which is based on Gaussian fitting was preseuted. Similar to the traditional registration method based on region, this method also used the gray information of images to build the similarity measure between two images and searched the point at which the similarity measure can reach its maximum or minimum to be the registration control points. Different with the traditional methods, it did not go straight for the extreme point and used it as the registration control point during the process of search, instead, the similarity-matrix was produced at first during the process of search and coefficients of Gaussian fitting function could be obtained from the value near the extreme points, the extreme points of Gaussian fitting function were used as the registration control points to complete the registration. The multiple sets of experimental results of hyperion high spectral registration all show that the method presented in the paper is more accurate than the traditional methods, and the registration accuracy reaches sub-pixel successfully, the method can meet the follow-up demands such as fusion, change detection and so on.