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

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,...

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Main Authors: Yuan Liang, Tao Su, Ruiqiu Wang, Jiangtao Liu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/11098653/
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author Yuan Liang
Tao Su
Ruiqiu Wang
Jiangtao Liu
author_facet Yuan Liang
Tao Su
Ruiqiu Wang
Jiangtao Liu
author_sort Yuan Liang
collection DOAJ
description 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.
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institution Kabale University
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publishDate 2025-01-01
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series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
spelling doaj-art-5165ee8e98504231aff2aa25a57f91e92025-08-22T23:08:07ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118204182044010.1109/JSTARS.2025.359338611098653OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment FeatureYuan Liang0https://orcid.org/0000-0001-5494-1250Tao Su1https://orcid.org/0000-0003-1529-4198Ruiqiu Wang2https://orcid.org/0009-0003-1040-9766Jiangtao Liu3National Laboratory of Radar Signal Processing, Xidian University, Xi’an, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an, ChinaSchool of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an, ChinaOptical-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.https://ieeexplore.ieee.org/document/11098653/Anisotropic diffusion filtering (ADF)maximum and minimum momentmultisource remote sensing images registration (MSRSIR)phase congruency (PC)synthetic aperture radar (SAR)
spellingShingle Yuan Liang
Tao Su
Ruiqiu Wang
Jiangtao Liu
OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Anisotropic diffusion filtering (ADF)
maximum and minimum moment
multisource remote sensing images registration (MSRSIR)
phase congruency (PC)
synthetic aperture radar (SAR)
title OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
title_full OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
title_fullStr OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
title_full_unstemmed OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
title_short OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature
title_sort os pcmm automatic registration algorithm for optical and sar image based on phase congruency and multimoment feature
topic Anisotropic diffusion filtering (ADF)
maximum and minimum moment
multisource remote sensing images registration (MSRSIR)
phase congruency (PC)
synthetic aperture radar (SAR)
url https://ieeexplore.ieee.org/document/11098653/
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