The inconsistent geometric distortion of Synthetic Aperture Radar (SAR) images when detecting from different angles makes multi-angle SAR image registration difficult. In this paper, the Demons algorithm, a non-rigid grey-scale based registration algorithm, is used for the first time in multi-angle SAR image registration. The algorithm calculates the displacement offset of the image to be aligned which influenced by the difference between the grey-scale of the reference image and the image to be aligned as well as the gradient of the reference image. Then Demons iteratively optimizes the offset through smooth interpolation with a Gaussian filter to ensure that image is accurately aligned. Three sets of SAR multi-angle images of different mountainous areas are used for experimental validation, and the analysis is carried out from both qualitative and quantitative metrics. The results show the Demons algorithm is more effective and more accurate than other non-rigid registration algorithms.
Due to the coherence of the scattering phenomenon, synthetic aperture radar (SAR) images are contaminated by multiplicative speckle noise, which seriously affects the interpretation and identification of SAR images. In this paper, we introduce the curvature filters which are realized by constructing tangent planes and correcting the regularization energy into speckle noise suppression of SAR images. Compared with the ROF model, the guided filter and some classic SAR image filtering algorithms (such as Lee filter), the curvature filters show strong competitiveness in the computing time, the peak signal-to-noise ratio (PSNR) and the structure similarity (SSIM) index. In addition, we compared the performance of the three curvature optimization models of the curvature filters, and found that the total variational filter model performs better in dealing with speckle noise of SAR images, which shows that the construction of local half-window and the assumption of piecewise constant for SAR images are robust to speckle noise suppression and structure preservation.
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