SAR and optical image matching based on phase consistency calculation and RS-GLOH descriptor

doi:10.7523/j.ucas.2022.007

Abstract

Abstract: In order to solve the difficulty in matching between synthetic aperture radar (SAR) and optical images due to nonlinear radiation differences and geometric differences, a new feature-based matching algorithm for SAR and optical images is proposed in this paper. This algorithm is mainly divided into three stages:feature extraction, feature description and feature matching. In the feature extraction stage, according to the nonlinear radiation difference between the two kinds of image, the minimum and maximum moment maps of SAR and optical images are obtained using the method based on phase consistency, and the minimum moment point and maximum moment point are obtained through extreme point detection and non-maximum suppression. In the feature description stage, in view of the nonlinear geometric difference between the two images, the ROEWA operator with good speckle noise suppression effects and Sobel operator are used to calculate the gradient amplitude and direction information of the SAR and optical images, respectively. Then gradient location orientation histogram (GLOH) is set up to describe the feature points (RS-GLOH). In the feature matching stage, method of combining the nearest neighbor matching (NNDR) and fast sampling consistency (FSC) is used to match the minimum and maximum moments respectively point. Experimental results show that the proposed method has excellent rotation and scale invariance. Compared with PSO-SIFT, SAR-SIFT, and OS-SIFT, more correct matching points and lower root mean square error (RMSE) can be obtained in 5 sets of SAR and optical image pairs in different regions.

Key words: SAR, optical, image matching, phase consistency, gradient location orientation histogram

CLC Number:

JI Hongwei, LIU Chang, PAN Zhigang, SHEN Fangyu. SAR and optical image matching based on phase consistency calculation and RS-GLOH descriptor[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(6): 788-799.

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