A Block-Based Multifeature Extraction Scheme for SAR Image Registration
Sourabh Paul, Umesh Chandra Pati · IEEE Geoscience and Remote Sensing Letters · 2018
In this letter, a block-based multifeature extraction scheme is proposed to register the synthetic aperture radar (SAR) images. With appropriate modifications, the scale-invariant feature transform (SIFT) and the SAR-SIFT operators are used to extract two types of features including texture points and corner points from the SAR images. The input images are divided into a certain number of blocks and the two types of features are extracted from each of the blocks for the uniform distribution of the features. A novel scheme is presented to obtain these features in the same proportion from the input images. The proposed method has the advantages of proper controllability of the number of extracted features and the uniform distribution of the features. A correct match identification by local searching algorithm is proposed to significantly increase the number of correct matches between the SAR images. Experiments on three pairs of multimodal and multitemporal SAR images demonstrate the effectiveness of the proposed method.