Decomposition Model With Background Dictionary Learning for Hyperspectral Target Detection

Representation-based target detectors for hyperspectral imagery have attracted considerable attention in recent years. However, their detection performance is still unsatisfactory due to the independent manner of the recovery process on each test pixel. Moreover, the background dictionary generated...

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Bibliographic Details
Published in:	IEEE journal of selected topics in applied earth observations and remote sensing Vol. 14; pp. 1872 - 1884
Main Authors:	Cheng, Tongkai, Wang, Bin
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Background dictionary learning (BDL) Background noise Components Computer applications Contamination Decomposition Detection Detectors Dictionaries Encoding Glossaries hyperspectral imagery Hyperspectral imaging Imagery Learning locality-constrained linear coding (LLC) Machine learning Minimization Object detection Pixels Recovery Signal processing Smoothness Target detection Target recognition total variation (TV) Windows (computer programs)
ISSN:	1939-1404, 2151-1535
Online Access:	Get full text
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