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30 August 2018 Synthetic aperture radar image registration based on hybrid feature detection and multifeature constraint matching
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Abstract
The alignment of images acquired using the synthetic aperture radar (SAR) is a central task in image processing for remote sensing. Owing to speckle noise and the particular features of SAR imaging, stable feature detection and accurate matching remain challenging tasks. We propose a registration method for SAR images. In feature detection, we develop a hybrid feature detection method to identify structural and textural features. A stable convex corner point feature is detected using stable convex polygons obtained by a proposed method for local stable extremal region extraction and convex polygon fitting. The stable local extremum points in each convex polygon are detected by an improved scale invariant feature transform method. In feature matching, a multifeature constraint matching method is designed for accurate matching. Coarse matching is implemented using the constraints on the region and its shape as well as the network. The use of stable local extremum points with spatial constraints can eliminate mismatches and yield a fine match. The results of experiments verified the effectiveness and accuracy of the proposed method.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2018/$25.00 © 2018 SPIE
Bo Pang, Qiuze Yu, Hong Sun, Wenshuai Xiao, Yong Xu, and Yan Zhang "Synthetic aperture radar image registration based on hybrid feature detection and multifeature constraint matching," Journal of Applied Remote Sensing 12(3), 036012 (30 August 2018). https://doi.org/10.1117/1.JRS.12.036012
Received: 3 January 2018; Accepted: 10 August 2018; Published: 30 August 2018
JOURNAL ARTICLE
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