Collaborative sparse reconstruction for pan-sharpening

Author

Xiao Xiang Zhu ; Grohnfeldt, Claas ; Bamler, Richard

Author_Institution

Remote Sensing Technol. Inst., German Aerosp. Center, Wessling, Germany

fYear

2013

fDate

21-26 July 2013

Firstpage

868

Lastpage

871

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.

Keywords

geophysical image processing; image fusion; image reconstruction; J-SparseFI algorithm; airborne HySpex hyperspectral data; airborne UltraCam data evaluation; collaborative sparse reconstruction; jointly sparse fusion of image algorithm; multispectral channel; pan-sharpening; signal structural correlation; statistic assessment; Dictionaries; Image reconstruction; Joints; Remote sensing; Sensors; Spatial resolution; HySpex; J-SparseFI; Joint Sparsity; Pan-Sharpening; SparseFI;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6721297

Filename

6721297