Dictionary Learning: From Data to Sparsity Via Clustering

Rajesh Bhatt, Venkatesh K. Subramanian

2015

Abstract

Sparse representation based image and video processing have recently drawn much attention. Dictionary learning is an essential task in this framework. Our novel proposition involves direct computation of the dictionary by analyzing the distribution of training data in the metric space. The resulting representation is applied in the domain of grey scale image denoising. Denoising is one of the fundamental problems in image processing. Sparse representation deals efficiently with this problem. In this regard, dictionary learning from noisy images, improves denoising performance. Experimental results indicate that our proposed approach outperforms the ones using K-SVD for additive high-level Gaussian noise while for the medium range of noise level, our results are comparable.

Paper Citation

in Harvard Style

Bhatt R. and K. Subramanian V. (2015). Dictionary Learning: From Data to Sparsity Via Clustering . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 635-640. DOI: 10.5220/0005573706350640

in Bibtex Style

@conference{icinco15,
author={Rajesh Bhatt and Venkatesh K. Subramanian},
title={Dictionary Learning: From Data to Sparsity Via Clustering},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={635-640},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005573706350640},
isbn={978-989-758-122-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Dictionary Learning: From Data to Sparsity Via Clustering
SN - 978-989-758-122-9
AU - Bhatt R.
AU - K. Subramanian V.
PY - 2015
SP - 635
EP - 640
DO - 10.5220/0005573706350640