Non-rigid image registration is an important preprocessing step in synthetic aperture radar (SAR) image applications. A crucial problem that involves in it is to reliably establish the correspondences between the feature points extracted from both the reference and sensed image. In this Letter, a non-rigid registration method is proposed to align two SAR images by registering two sets of feature points extracted from the images. In the proposed method, both point-wise background regional similarity and local spatial constraint are utilised to find correct correspondences between two feature point sets. Point-wise background regional similarity is introduced to enhance feature points similarity measurement. Meanwhile, based on the adjacent spatial relationship between feature point and its neighbouring points, a new concept of local spatial constraint is further proposed to robustly characterise the geometric consistency between them, which is designed to reduce the ambiguous matches aroused by speckle noise and feature outliers. By combining these two improvements, the authors generate a new matching cost function and formulate non-rigid image registration as a correspondence optimisation problem, which can be solved by the probabilistic relaxation method. Experimental results on both simulated and real deformed SAR images indicate the robustness and effectiveness of the proposed method.

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Non-rigid synthetic aperture radar image registration by combining point-wise background regional similarity and local spatial constraint

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