Image fusion and reconstruction of compressed data: A joint approach

Daniele Picone 1 Laurent Condat 2 Florian Cotte 3 Mauro Dalla Mura 1
1 GIPSA-SIGMAPHY - SIGMAPHY
GIPSA-DIS - Département Images et Signal
2 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
3 GIPSA-CICS - CICS
GIPSA-DIS - Département Images et Signal
Abstract : In the context of data fusion, pansharpening refers to the combination of a panchromatic (PAN) and a multispectral (MS) image, aimed at generating an image that features both the high spatial resolution of the former and high spectral diversity of the latter. In this work we present a model to jointly solve the problem of data fusion and reconstruction of a compressed image; the latter is envisioned to be generated solely with optical on-board instruments, and stored in place of the original sources. The burden of data downlink is hence significantly reduced at the expense of a more laborious analysis done at the ground segment to estimate the missing information. The reconstruction algorithm estimates the target sharpened image directly instead of decompressing the original sources beforehand; a viable and practical novel solution is also introduced to show the effectiveness of the approach.
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Communication dans un congrès
IEEE International Conference on Image Processing (ICIP), Oct 2018, Athens, Greece
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Soumis le : lundi 30 juillet 2018 - 12:18:52
Dernière modification le : lundi 20 août 2018 - 15:45:31

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Daniele Picone, Laurent Condat, Florian Cotte, Mauro Dalla Mura. Image fusion and reconstruction of compressed data: A joint approach. IEEE International Conference on Image Processing (ICIP), Oct 2018, Athens, Greece. 〈hal-01851515〉

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