Low-dimensional multiscale fast SAR image registration method

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Synthetic aperture radar (SAR) has developed in leaps and bounds over the past decades, which makes rapid revisit and high-frequency coverage feasible. However, accurate and efficient registration of the SAR image is still a challenging task. Many existing SAR image registration methods major in describing detected features in a unique, identifiable, but maybe complex way. These descriptors are usually high-dimensional, resulting in increased computational complexity. To this end, a low-dimensional multiscale fast method for SAR image registration is proposed in this paper. First, the candidate points are detected in the modulus map of phase congruency (PC). This operation is robust to speckle noise in SAR images and improves the repeatability of feature points. Second, circular neighbourhoods of each point are extracted in multiple scales to describe their features with the maximum index map (MIM). Note that we condense the feature information of candidate points in the whole neighbourhood in an intensity-order way, which significantly reduces the dimensionality of the descriptors. Overall, the proposed method focuses on efficient representation of point features, thus allowing more feature points to be detected and involved in the subsequent high-speed feature matching. Experiments on raw SAR images with neither prior information nor any pre-processing measure like terrain correction and de-speckling demonstrate the efficacy of the proposed method over other state-of-the-art SAR image registration algorithms. Some analyses concerning the factors affecting feature matching and invariance of PC map and MIM are also studied.