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Sparse coding can exploit the intrinsic sparsity of hyperspectral images (HSIs) by representing it as a group of sparse codes. This strategy has been shown to be effective for HSI denoising. However, how to effectively exploit the structural information within the sparse codes (structured sparsity) has not been widely studied. In this paper, we propose a new method for HSI denoising, which uses structured...
Sparse coding provides an excellent image prior for hyperspectral images (HSIs) denoising. However, on one hand, it is challenging to capture the structure within each sparse code for improving the reconstruction accuracy, on the other hand, the inconsistent recovery of the sparse codes corrupts the spectrum similarity in each homogeneous cluster of the HSI. To address these problems, we first propose...
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