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Synthetic aperture radar image registration based on hybrid feature detection and multifeature constraint matching

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.