Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/327203
Type: Artigo
Title: Learning Dictionaries As A Sum Of Kronecker Products
Author: Dantas
Cassio Fraga; da Costa
Michele N.; Lopes
Renato da Rocha
Abstract: The choice of an appropriate frame, or dictionary, is a crucial step in the sparse representation of a given class of signals. Traditional dictionary learning techniques generally lead to unstructured dictionaries that are costly to deploy and train, and do not scale well to higher dimensional signals. In order to overcome such limitation, we propose a learning algorithm that constrains the dictionary to be a sum of Kronecker products of smaller subdictionaries. This approach, named sum of Kronecker products, is demonstrated experimentally in an image denoising application.
Subject: Alternating Direction Method Of Multipliers
(admm)
Dictionary Learning
Image Denoising
Kronecker Product
K-svd
Nuclear Norm
Separable Dictionaries
Editor: IEEE-Inst Electrical Electronics Engineers Inc
Piscataway
Rights: fechado
Identifier DOI: 10.1109/LSP.2017.2681159
Address: http://ieeexplore.ieee.org.ez88.periodicos.capes.gov.br/document/7875507/
Date Issue: 2017
Appears in Collections:Unicamp - Artigos e Outros Documentos

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