Collaborative sparse reconstruction for pan-sharpening

Xiao Xiang Zhu, Claas Grohnfeldt, Richard Bamler

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

5 Scopus citations

Abstract

In this paper, we extend the Sparse Fusion of Images (SparseFI, pronounced 'sparsify') algorithm, proposed by the authors before, to a Jointly Sparse Fusion of Images (J-SparseFI) algorithm by exploiting the possible signal structural correlations between different multispectral channels. The algorithm is evaluated using airborne UltraCam data. The superior performance of the proposed methods has been demonstrated by a statistic assessment. Moreover, first experimental result using airborne HySpex hyperspectral data is presented.

Original languageEnglish
Title of host publication2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Pages868-871
Number of pages4
DOIs
StatePublished - 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

Keywords

  • HySpex
  • J-SparseFI
  • Joint Sparsity
  • Pan-Sharpening
  • SparseFI

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