Abstract:This paper addresses the problem of impulse denoising from hyper-spectral images. Impulse noise is sparse; removing impulse noise requires minimizing an Irnorm data fidelity term. Prior studies have exploited the intra band spatial correlation (leading to sparsity in transform domain) and inter-band spectral-correlation Uoint sparsity) of hyper-spectral images for Gaussian denoising. In this work, we propose to learn the joint-sparsity promoting dictionary adaptively from the data for impulse denoising problem… Show more
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