Shift-invariant sparse representation of images using learned dictionaries

Jayaraman J. Thiagarajan; Karthikeyan N. Ramamurthy; Andreas Spanias

doi:10.1109/MLSP.2008.4685470

Shift-invariant sparse representation of images using learned dictionaries

Jayaraman J. Thiagarajan, Karthikeyan N. Ramamurthy, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

24 Scopus citations

Abstract

Sparse approximations that are evaluated using overcomplete learned dictionaries are useful in many image processing applications such as compression, denoising and feature extraction. Incorporating shift invariance into sparse representation of images can improve sparsity while providing a good approximation. The K-SVD algorithm adapts the dictionary based on a set of training examples, without shift invariance constraints. This paper presents two algorithms for training dictionaries and evaluating shift-invariant sparse representations for image data. One is a modified version of the K-SVD algorithm and the other is a novel graph-based algorithm that adapts the dictionary and computes representations using a low complexity reconstruction procedure.

Original language	English (US)
Title of host publication	Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Pages	145-150
Number of pages	6
DOIs	https://doi.org/10.1109/MLSP.2008.4685470
State	Published - 2008
Event	2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 - Cancun, Mexico Duration: Oct 16 2008 → Oct 19 2008

Publication series

Name	Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Other

Other	2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Country/Territory	Mexico
City	Cancun
Period	10/16/08 → 10/19/08

ASJC Scopus subject areas

Artificial Intelligence
Software
Electrical and Electronic Engineering

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10.1109/MLSP.2008.4685470

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Thiagarajan, J. J., Ramamurthy, K. N., & Spanias, A. (2008). Shift-invariant sparse representation of images using learned dictionaries. In Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 (pp. 145-150). Article 4685470 (Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008). https://doi.org/10.1109/MLSP.2008.4685470

Shift-invariant sparse representation of images using learned dictionaries. / Thiagarajan, Jayaraman J.; Ramamurthy, Karthikeyan N.; Spanias, Andreas.
Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008. 2008. p. 145-150 4685470 (Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Thiagarajan, JJ, Ramamurthy, KN & Spanias, A 2008, Shift-invariant sparse representation of images using learned dictionaries. in Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008., 4685470, Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008, pp. 145-150, 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008, Cancun, Mexico, 10/16/08. https://doi.org/10.1109/MLSP.2008.4685470

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Shift-invariant sparse representation of images using learned dictionaries

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