SAR Image Registration Using Multiscale Image Patch Features With Sparse Representation

In this paper, we propose a new image registration method for synthetic aperture radar (SAR) image with multiscale image patch features, in which the sparse representation technique is exploited. Considering the influence of speckle noise on feature extraction, in the proposed method, a spatial correlation strategy based on stationary wavelet transform is adopted to select the reliable feature points from the initial scale invariant feature transform keypoints in the reference image. By introducing multiscale image patch, a new feature descriptor is further designed to describe the attribute domain of feature points for higher discrimination. The corresponding points in the sensed image are established based on the minimum discrepancy criterion calculated by the sparse representation technique. Moreover, the local geometric consistency among a feature point and its nearest neighbor points is employed to remove the mismatches from the tentative matches. Twenty-two pairs of SAR images acquired under various conditions are utilized to validate the effectiveness of the proposed method. Compared with the traditional SAR image registration methods, the results show that the proposed method is competent to improve the registration performance substantially.