Analysis dictionary learning based on Nesterov's gradient with application to SAR image despeckling

Dong, J and Wang, W (2014) Analysis dictionary learning based on Nesterov's gradient with application to SAR image despeckling

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Abstract

We focus on the dictionary learning problem for the analysis model. A simple but effective algorithm based on Nesterov's gradient is proposed. This algorithm assumes that the analysis dictionary contains unit ℓ norm atoms and trains the dictionary iteratively with Nesterov's gradient. We show that our proposed algorithm is able to learn the dictionary effectively with experiments on synthetic data. We also present examples demonstrating the promising performance of our algorithm in despeckling synthetic aperture radar (SAR) images. © 2014 IEEE.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Divisions :	Surrey research (other units)
Authors :	Dong, J and Wang, W
Date :	2014
DOI :	10.1109/ISCCSP.2014.6877922
Depositing User :	Symplectic Elements
Date Deposited :	28 Mar 2017 13:12
Last Modified :	23 Jan 2020 13:07
URI:	http://epubs.surrey.ac.uk/id/eprint/806092

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