Adapted Anisotropic Gaussian SIFT for SAR Registration
In this letter, we propose an adapted anisotropic Gaussian scale-invariant feature transform (AAG-SIFT) method to find feature matches for synthetic aperture radar (SAR) image registration. First, features are detected and described in an AAG scale space. The scale space is built adaptively to local structures. Noises are blurred, but details and edges remain unaffected in this scale space.
Compared with traditional SIFT-based matching methods, features extracted by AAG-SIFT are more stable and precise. Then, the dominant orientation consistency (DOC) property is analyzed and adopted to improve the matching stability. The correct matching rate is significantly increased by DOC matching. Experiments on various SAR images demonstrate the applicability of AAG-SIFT to find stable and precise feature matches for SAR registration.
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