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Sparse representation (SR)-based SAR imaging approaches have shown their superior performance compared with conventional approaches. However, for an image with rich spatial structures, a fixed global dictionary is usually ineffective to characterize the local structures. Piecewise autoregressive (PAR) model indicates that each pixel can be linearly represented by its local neighboring pixels. Inspired...
SR-based denoising methods have shown promising performance in image denoising. However, Because of the degradation of the noisy image, conventional SR based denoising models may not be accurate enough for the reconstruction of a clean image. Therefore, to reduce the noise corruption, a novel adaptive sparse representation based SAR image despeckling algorithm is proposed in this paper, where the...
Chirp scaling algorithm (CSA) is one of the most popular algorithms in radar imaging, due to its excellent focusing ability and implementation simplicity. However, such superior performance, especially the resolution capability is greatly restricted by the number of observed measurements. Specially, if the measurements are reduced, images with high sidelobes and lower resolution are formed. The recent...
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