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Nonconvex regularization in remote sensing


Tuia, Devis; Flamary, Rémi; Barlaud, Michel (2016). Nonconvex regularization in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 54(11):6470-6480.

Abstract

In this paper, we study the effect of different regularizers and their implications in high-dimensional image classification and sparse linear unmixing. Although kernelization or sparse methods are globally accepted solutions for processing data in high dimensions, we present here a study on the impact of the form of regularization used and its parameterization.We consider regularization via traditional squared (!2) and sparsity-promoting (!1) norms, as well as more unconventional non convex regularizers (!p and log sum penalty). We compare their properties and advantages on several classification and linear unmoving tasks and provide advices on the choice of the best regularizer for the problemat hand. Finally,we also provide a fully functional toolbox for the community.

Abstract

In this paper, we study the effect of different regularizers and their implications in high-dimensional image classification and sparse linear unmixing. Although kernelization or sparse methods are globally accepted solutions for processing data in high dimensions, we present here a study on the impact of the form of regularization used and its parameterization.We consider regularization via traditional squared (!2) and sparsity-promoting (!1) norms, as well as more unconventional non convex regularizers (!p and log sum penalty). We compare their properties and advantages on several classification and linear unmoving tasks and provide advices on the choice of the best regularizer for the problemat hand. Finally,we also provide a fully functional toolbox for the community.

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1 citation in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2016
Deposited On:10 Oct 2016 06:59
Last Modified:08 Dec 2017 20:29
Publisher:Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Publisher DOI:https://doi.org/10.1109/TGRS.2016.2585201

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