OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature

Abstract

Optical-SAR image registration has wide applications in change detection and disaster early warning. However, the significant differences in noise characteristics and radiometric properties between the two types of images remain major challenges for achieving accurate registration. In this article, we propose an automatic registration algorithm for optical and SAR images based on phase congruency and multimoment features. First, a multiangle bandwidth log-Gabor filter bank is designed to enhance structural details and extract phase congruency information. Based on the enhanced phase congruency map, we compute the maximum and minimum moment maps (MaxMM and MinMM) from the phase congruency responses, which, respectively, capture salient edge and corner features that are robust to radiometric and geometric variations. A novel feature detection strategy is applied on these moment maps, followed by a voting mechanism to select highly stable keypoints. For feature description, we introduce the multimoment orientation histogram, which concatenates histograms computed from MaxMM and MinMM, significantly improving both robustness and distinctiveness in heterogeneous image matching. Comprehensive experiments on real-world multisource datasets demonstrate that the proposed OS-PCMM algorithm achieves superior accuracy and robustness compared to state-of-the-art methods.

Keywords

• Anisotropic diffusion filtering (ADF)
• maximum and minimum moment
• multisource remote sensing images registration (MSRSIR)
• phase congruency (PC)
• synthetic aperture radar (SAR)