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Proximal approach to denoising hyperspectral images under mixed-noise model
2020
IET Image Processing
The authors present a proximal approach to hyperspectral image denoising adapted to the mixed noise behaviour of hyperspectral data; named hyperspectral image proximal denoiser (HSIProxDenoiser). A combination of Gaussian-impulse noise has been handled under maximum a posteriori framework using two data fidelity terms. They have incorporated prior information about the data in the form of two regularisation terms, namely Tikhonov-Miller (TM) and total variation (TV). Since TV possesses feature
doi:10.1049/iet-ipr.2019.1763
fatcat:fm3wttchqrgj3fulxkmho7xobe