A novel local pettern based self-similarity descriptor for multisource remote sensing image registration

摘要

This paper proposed a novel local feature descriptor for multisource remote sensing image matching that is robust to significant geometric and illumination differences. In the proposed registration method, traditional SIFT algorithm is applied for local feature extraction and a novel descriptor, named local order pattern based self-similarity descriptor, LOPSS descriptor, is constructed for each extracted feature point. Then, a matching process followed by a reliable outlier removal procedure is implemented for feature matching and mismatch elimination. Finally, registration parameters are estimated by least square method in the affine transformation. The proposed method is applied for matching multisource remote sensing image pairs and the results verify its robustness and discriminability.