Clustering K-SVD for sparse representation of images

K-singular value decomposition (K-SVD) is a frequently used dictionary learning (DL) algorithm that iteratively works between sparse coding and dictionary updating. The sparse coding process generates sparse coefficients for each training sample, and the sparse coefficients induce clustering feature...

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Bibliographic Details
Published in:	EURASIP journal on advances in signal processing Vol. 2019; no. 1; pp. 1 - 14
Main Authors:	Fu, Jun, Yuan, Haikuo, Zhao, Rongqiang, Ren, Luquan
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 25.10.2019 Springer Springer Nature B.V SpringerOpen
Subjects:	Algorithms Atomic properties Clustering Coding Dictionaries Dictionary learning Engineering Equipment and supplies Greedy algorithms Image processing Machine learning Quantum Information Technology Representations Signal,Image and Speech Processing Singular value decomposition Sparse representation Spintronics Image processing Sparse representation Dictionary learning
ISSN:	1687-6180, 1687-6172, 1687-6180
Online Access:	Get full text
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