Description of Salient Features Combined with Local Self-Similarity for SAR Image Registration

Abstract

Local feature descriptor plays an important role in image representation and is helpful to further image processing. This paper proposes a local feature descriptor based registration method for synthetic aperture radar (SAR) images. The proposed method starts with identifying evenly distributed features by applying the divided salient image disk (SID) extraction method. To describe the shape content of local neighborhood, local self-similarity (LSS) descriptor is built in the local normalized region with a suitable size for every detected feature. Finally, the correspondence is found by measuring the similarity between LSS descriptors. The registration experiments on SAR images demonstrate that the proposed method can be applied to SAR image registration.