Hyperspectral Image Denoising via Group Sparsity Regularized Hybrid Spatio-Spectral Total Variation

Hyperspectral Image Denoising via Group Sparsity Regularized Hybrid Spatio-Spectral Total Variation

In this paper, we propose a new hyperspectral image (HSI) denoising model with the group sparsity regularized hybrid spatio-spectral total variation (GHSSTV) and low-rank tensor decomposition, which is based on the analysis of structural sparsity of HSIs. First, the global correlations among all mod...

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Bibliographic Details
Main Authors: Pengdan Zhang, Jifeng Ning
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Remote Sensing
Subjects:
mixed noise
Tucker decomposition
alternating direction multiplier method (ADMM)
hyperspectral image denoising
Online Access:https://www.mdpi.com/2072-4292/14/10/2348

Internet

https://www.mdpi.com/2072-4292/14/10/2348

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