Anomaly detection in hyperspectral images based on low-rank and sparse representation

IEEE Transactions on Geoscience and Remote Sensing

Volumn 54, Issue 4, 2016, Pages 1990-2000

  Xu, Yang ^a   Wu, Zebin ^a,b   Li, Jun ^c   Plaza, Antonio ^b   Wei, Zhihui ^a  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b UNIVERSITY OF EXTREMADURA   (Spain)

^c SUN YAT SEN UNIVERSITY   (China)

Author keywords

Anomaly detection; Dictionary construction; Hyperspectral image (HSI) analysis; Low rank representation (LRR); Sparse representation

Indexed keywords

MATRIX ALGEBRA; SIGNAL DETECTION; SPECTROSCOPY;

DICTIONARY CONSTRUCTIONS; GLOBAL AND LOCAL STRUCTURES; HYPERSPECTRAL IMAGES; LOW-RANK MATRICES; LOW-RANK REPRESENTATIONS; REGULARIZATION TERMS; RESIDUAL MATRICES; SPARSE REPRESENTATION;

PIXELS;

ALGORITHM; ANOMALY; DATA MINING; DATA SET; IMAGE ANALYSIS; NUMERICAL METHOD; PIXEL; RANKING;

EID: 84946950059     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2493201     Document Type: Article

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