Low-Rank and Sparse Representation for Hyperspectral Image Processing: A Review

被引：115
|
作者：
Peng, Jiangtao [1 ]
Sun, Weiwei [2 ]
Li, Heng-Chao [3 ]
Li, Wei [4 ,5 ]
Meng, Xiangchao [6 ]
Ge, Chiru [3 ]
Du, Qian [7 ]
机构：
[1] Hubei Univ, Hubei Key Lab Appl Math, Fac Math & Stat, Wuhan 430062, Peoples R China
[2] Ningbo Univ, Dept Geog & Spatial Informat Tech, Ningbo 315211, Peoples R China
[3] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu, Peoples R China
[4] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China
[5] Beijing Key Lab Fract Signals & Syst, Beijing 100081, Peoples R China
[6] Ningbo Univ, Fac Elect Engn & Comp Sci, Ningbo 315211, Peoples R China
[7] Mississippi State Univ, Dept Elect & Comp Engn, Starkville, MS 39762 USA
来源：
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE | 2022年 / 10卷 / 01期
基金：
中国国家自然科学基金; 北京市自然科学基金;
关键词：
Tensors; Noise reduction; Sparse matrices; Dictionaries; Matrix decomposition; Machine learning; Kernel; NONNEGATIVE MATRIX FACTORIZATION; WEIGHTED NUCLEAR NORM; JOINT SPARSE; BAND SELECTION; DIMENSIONALITY REDUCTION; TENSOR DECOMPOSITION; MULTISPECTRAL IMAGES; NOISE-REDUCTION; CLASSIFICATION; KERNEL;
D O I：
10.1109/MGRS.2021.3075491
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Combining rich spectral and spatial information, a hyperspectral image (HSI) can provide a more comprehensive characterization of the Earth's surface. To better exploit HSIs, a large number of algorithms have been developed during the past few decades. Due to their very high correlation between spectral channels and spatial pixels, HSIs have intrinsically sparse and low-rank structures. The sparse representation (SR) and low-rank representation (LRR)-based methods have proven to be powerful tools for HSI processing and are widely used in different HS fields. In this article, we present a survey of low-rank and sparse-based HSI processing methods in the fields of denoising, superresolution, dimension reduction, unmixing, classification, and anomaly detection. The purpose is to provide guidelines and inspiration to practitioners for promoting the development of HSI processing. For a listing of the key terms discussed in this article, see 'Nomenclature.' © 2013 IEEE.
引用
收藏
页码：10 / 43
页数：34
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