Paper Info
Title
SAR Image Registration Based on ROEWA-Blocks and Multiscale Circle Descriptor
Abstract
Given the imaging characteristics of synthetic aperture radar (SAR) images and the inherent speckle noise in them, scale-invariant feature transform based algorithms are unable to perform satisfactorily. To improve registration efficiency between SAR images, we propose a robust and efficient registration method with three main contributions. First, considering sudden dark patches appearing in SAR images, we propose the ratio of exponentially weighted average blocks to suppress the sudden dark patches and better adapt to different test images. This new operator called blocks of the ratio of exponentially weighted averages (ROEWA-B) divides the processing windows of ROEWA into blocks, which can not only reduce speckle noise but also retain more edge details compared to ROEWA when sudden dark patches appear. Second, for outlier removal, we present an approach using the minimum moment map to remove erroneous keypoints. Finally, based on the gradient location orientation histogram descriptor, we propose a novel multiscale circle descriptor, which combines scale change information to give weights to feature points at different scales. Experimental results for various thresholds and evaluations demonstrate the advantage and robustness of our method in registration.
Year
DOI
Venue
2021
10.1109/JSTARS.2021.3119923
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Keywords
DocType
Volume
Radar polarimetry, Feature extraction, Speckle, Image edge detection, Synthetic aperture radar, Robustness, Manganese, Multiscale descriptor, multiscale space, ratio of exponentially weighted averages (ROEWA), synthetic aperture radar (SAR) image
Journal
14
ISSN
Citations 
PageRank 
1939-1404
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Yameng Hong101.01
Chengcai Leng201.35
Xinyue Zhang300.68
Huaiping Yan401.01
Jinye Peng528440.93
Licheng Jiao600.34
Irene Cheng7584.40
Anup Basu874997.26