Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition

Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition

Hyperspectral image (HSI) is usually corrupted by various types of noise, including Gaussian noise, impulse noise, stripes, deadlines, and so on. Recently, sparse and low-rank matrix decomposition (SLRMD) has demonstrated to be an effective tool in HSI denoising. However, the matrix-based SLRMD tech...

Full description

Bibliographic Details
Main Authors: Zhihong Huang, Shutao Li, Leyuan Fang, Huali Li, Jon Atli Benediktsson
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Hyperspectral image
denoising
sparse and low-rank tensor decomposition
nonlocal similarity
Online Access:https://ieeexplore.ieee.org/document/8125087/

Internet

https://ieeexplore.ieee.org/document/8125087/

Similar Items