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In this paper a new hyperspectral image based on wavelets and sparse regularization is proposed. This new method is called Wavelet Based Sparse Restoration (WBSR). The hyperspectral signal is restored by utilizing penalized least squares and the `1 penalty. Iterative Soft Thresholding (IST) algorithm is used to solve the convex optimization problem. It is shown that not only WBSR improves the denioising results both visually and based on Signal to Noise Ratio (SNR) but also increases the classification accuracies.
Rasti et al. (Thu,) studied this question.