TY - GEN
T1 - A new approach to sparse image representation using MMV and K-SVD
AU - Yang, Jie
AU - Bouzerdoum, Abdesselam
AU - Phung, Son Lam
PY - 2009
Y1 - 2009
N2 - This paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogonal matching pursuit MMV (OMPMMV) methods, the proposed method runs faster and achieves a higher overall reconstruction accuracy.
AB - This paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogonal matching pursuit MMV (OMPMMV) methods, the proposed method runs faster and achieves a higher overall reconstruction accuracy.
UR - http://www.scopus.com/inward/record.url?scp=70549113670&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04697-1_19
DO - 10.1007/978-3-642-04697-1_19
M3 - Conference contribution
AN - SCOPUS:70549113670
SN - 3642046967
SN - 9783642046964
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 200
EP - 209
BT - Advanced Concepts for Intelligent Vision Systems - 11th International Conference, ACIVS 2009, Proceedings
T2 - 11th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2009
Y2 - 28 September 2009 through 2 October 2009
ER -