Improved method for SAR image registration based on scale invariant feature transform

Deyun Zhou, Lina Zeng, Junli Liang, Kun Zhang

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Scale invariant feature transform (SIFT) is one of the most common registration algorithms for synthetic aperture radar (SAR) images. However, the occurrence of speckle noise and geometric distortion within SAR images usually leads to limited effectiveness, challenging the stability of SIFT and its variants in real actual applications. In this study, significant improvements for SAR image registration with SIFT are made, which lie mainly in two aspects. First, a scheme is developed to enhance the description of keypoints with improved dominant orientation assignment and support region. Second, an optimised matching method for further enhancing the matching performance is developed to reduce the mutual interference among the keypoints with similar location and dominant orientations. Extensive experiments confirm the effectiveness of the proposed algorithm for SAR images.

Original languageEnglish
Pages (from-to)579-585
Number of pages7
JournalIET Radar, Sonar and Navigation
Volume11
Issue number4
DOIs
StatePublished - 1 Apr 2017

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