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Coherence Regularized Dictionary Learning
Conference

Coherence Regularized Dictionary Learning

Abstract

Sparse representations over redundant learned dictionaries have shown to produce high quality results in various image processing tasks. An important characteristic of a learned dictionary is the mutual coherence of dictionary that affects its generalization performance and the optimality of sparse codes generated from it. In this paper, we present a dictionary learning model equipped with coherence regularization. For this model, two novel …

Authors

Nejati M; Samavi S; Soroushmehr SMR; Najarian K

Pagination

pp. 4717-4721

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

March 1, 2016

DOI

10.1109/icassp.2016.7472572

Name of conference

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)