A Uniform SIFT-Like Algorithm for SAR Image Registration

In this letter, a uniform scale-invariant feature transform (SIFT)-like algorithm is proposed for synthetic aperture radar (SAR) image registration, which can extract enough robust, reliable, and uniformly distributed features by the strategies of optimal feature selection based on a Voronoi diagram and feature scale-space proportional extraction. SAR images, taken from different viewpoints by an airborne sensor and at different times by spaceborne sensors, were used as test data to validate the effectiveness of the proposed algorithm. The indexes of local density and global coverage were used to assess the spatial distribution of matches. Compared with the traditional SIFT-like algorithm for SAR images (SAR-SIFT), the results show that the proposed algorithm can increase the number of matches and optimize their spatial distribution.