DocumentCode :
1893001
Title :
Compressive sensing for image fusion - with application to pan-sharpening
Author :
Zhu, Xiao Xiang ; Wang, Xuan ; Bamler, Richard
Author_Institution :
Lehrstuhl fur Methodik der Fernerkundung, Tech. Univ. Munchen, Munich, Germany
fYear :
2011
fDate :
24-29 July 2011
Firstpage :
2793
Lastpage :
2796
Abstract :
Data provided by most optic earth observation satellites such as IKONOS, Quick Bird and GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and several multispectral channels at a lower spatial resolution (LR). The fusion of a HR panchromatic and the corresponding LR spectral channels is called "pan-sharpening". It aims at obtaining a high resolution multispectral image. In this paper, we propose a new sophisticated pan-sharpening method named Sparse Fusion of Images (SparseFI, pronounced as sparsify). SparseFI is based on the compressive sensing theory and explore the sparse representation of HR/LR multispectral image patches in the dictionaries pairs co-trained from the panchromatic image and its corresponding down-sampled version. Compared to other methods it "learns" from, i.e. adapts itself to, the data and has better performance than existing methods. Due to the fact that the SparseFI algorithm does not assume any model of the panchromatic image and thanks to the super-resolution capability and robustness of compressive sensing, it gives higher spatial and spectral resolution with less spectral distortion compared to the conventional methods.
Keywords :
geophysical image processing; geophysical techniques; image fusion; image resolution; GeoEye satellite; HR multispectral image patches; IKONOS satellite; LR multispectral image patches; Quick Bird satellite; high resolution multispectral image; high spatial resolution; low spatial resolution spectral channel; multispectral channels; pan-sharpening method; panchromatic channel; panchromatic image; sparse image fusion; sparseFI algorithm; spectral distortion; Compressed sensing; Dictionaries; Image fusion; Image reconstruction; Remote sensing; Spatial resolution; compressive sensing; dictionary training; pan-sharpening; sparse coefficients estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
ISSN :
2153-6996
Print_ISBN :
978-1-4577-1003-2
Type :
conf
DOI :
10.1109/IGARSS.2011.6049794
Filename :
6049794
Link To Document :
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