Pansharpening via sparsity optimization using overcomplete transforms

Frosti Palsson, Johannes R. Sveinsson, Magnus O. Ulfarsson, Jon A. Benediktsson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this paper we consider pansharpening of multispectral satellite imagery based on solving an under-determined inverse problem regularized by the ℓ1-norm of the coefficients of overcomplete multi-scale transforms which all are tight-frame systems. There are two main approaches in sparsity promoting ℓ1-norm regularization, the analysis and the synthesis approach. We perform a number of experiments using two real and well known datasets where the focus is the comparison of the two approaches. One dataset includes a high resolution reference image while the other needs to be degraded prior to pansharpening in order to use the original multispectral image as the reference. Experiments are performed for a range of values for the regularization parameter, where each resulting pansharpened image is evaluated using three quality metrics. The behavior of those metrics as a function of the regularization parameter is compared for the analysis and synthesis formulations and it is shown that analysis gives better results.

Original languageEnglish
Title of host publication2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Pages856-859
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Melbourne, VIC, Australia
Duration: 21 Jul 201326 Jul 2013

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period21/07/1326/07/13

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