Hyperspectral Mixed Denoising via Spectral Difference-Induced Total Variation and Low-Rank Approximation

Hyperspectral Mixed Denoising via Spectral Difference-Induced Total Variation and Low-Rank Approximation

Exploration of multiple priors on observed signals has been demonstrated to be one of the effective ways for recovering underlying signals. In this paper, a new spectral difference-induced total variation and low-rank approximation (termed SDTVLA) method is proposed for hyperspectral mixed denoising...

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Bibliographic Details
Main Authors: Le Sun, Tianming Zhan, Zebin Wu, Liang Xiao, Byeungwoo Jeon
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Remote Sensing
Subjects:
hyperspectral mixed denoising
total variation
low-rank approximation
spectral difference space
ADMM
Online Access:https://www.mdpi.com/2072-4292/10/12/1956

Internet

https://www.mdpi.com/2072-4292/10/12/1956

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