Matching Conjugate Points between Multi Resolution Satellite Images Using Geometric and Radiometric Properties

Remotely sensed images are the main source for a variety of mapping and change detection applications. Images from different satellites are employed in several of these applications. However, each type of these images has different resolution and orientation. Hence, they need to be co-registered before any meaningful utilization. The first step in the registration process is to find conjugate points between the images. This paper presents a modified approach of Scott and Longuet-Higgins approach to find conjugate points between different remotely sensed images. In such an algorithm, initially , corner points are extracted automatically in two images, and for each pair of points a cost value is computed. The cost of corresponding any two points is computed using image coordinates and pixel intensities. The cost values are then used to fill a cost matrix, and its SVD is used to find correspondent points. The algorithm is tested on three pairs of satellite images with different resolutions and orientations. Result shows that the presented approach succeeded in finding more than 96% of conjugate points between two different satellite images using only the image coordinates. Moreover, result shows that including the image intensities in the matching procedure does not improve the results significantly.