Title
OS-PC: Combining Feature Representation and 3-D Phase Correlation for Subpixel Optical and SAR Image Registration
Abstract
Phase correlation (PC), an efficient frequency-domain registration method, has been extensively used in remote sensing images owing to its subpixel accuracy and robustness to image contrast, noise, and occlusions. However, its performance becomes poor when applied to the registration between optical and synthetic aperture radar (SAR) images, which are two typical multisensor images. Inspired by the recently proposed feature-based methods, we present a novel subpixel registration method that combines robust feature representations of optical and SAR images and the 3-D PC (OS-PC). The robust feature representations, which capture the inherent property of the two images and retain their structural information, form two dense image cubes. The 3-D PC utilizes the image cubes as a substitute of two raw images to estimate 2-D translations, either by locating peak in the spatial domain or by directly working in the Fourier domain. Furthermore, we investigate two techniques to improve the accuracy of the 3-D PC both in the spatial domain and Fourier domain: the first is the constrained energy minimization method to seek the Dirac delta function after 3-D inverse Fourier transform and the second is the fast sample consensus fitting to estimate phase difference after high-order singular value decomposition of the PC matrix. Experiments with both simulated and satellite optical-to-SAR pairs were carried out to test the proposed method. Compared with state-of-the-art PC methods and optical-to-SAR registration methods, the proposed method presents a superior performance in both accuracy and robustness. Moreover, we verify the adaptability of the proposed method.
Year
DOI
Venue
2020
10.1109/TGRS.2020.2976865
IEEE Transactions on Geoscience and Remote Sensing
Keywords
DocType
Volume
Feature representation,image registration,optical,phase correlation (PC),synthetic aperture radar (SAR),subpixel
Journal
58
Issue
ISSN
Citations 
9
0196-2892
2
PageRank 
References 
Authors
0.35
0
5
Name
Order
Citations
PageRank
Yuming Xiang1156.30
Rongshu Tao221.36
Ling Wan361.41
Feng Wang4193.05
Hongjian You510317.44