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Pansharpening by Convolutional Neural Networks

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Masi, Giuseppe, Cozzolino, Davide, Verdoliva, Luisa, Scarpa, Giuseppe·2016·Remote Sensing
DOI 10.3390/rs8070594
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Abstract

A new pansharpening method is proposed, based on convolutional neural networks. We adapt a simple and effective three-layer architecture recently proposed for super-resolution to the pansharpening problem. Moreover, to improve performance without increasing complexity, we augment the input by including several maps of nonlinear radiometric indices typical of remote sensing. Experiments on three representative datasets show the proposed method to provide very promising results, largely competitive with the current state of the art in terms of both full-reference and no-reference metrics, and also at a visual inspection.

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Metadata

Authors
Masi, G., Cozzolino, D., Verdoliva, L., & Scarpa, G.
Venue
Remote Sensing
Publisher
MDPI AG
Published
2016-07-14
Volume
8
Issue
7
Pages
594
ISSN
2072-4292 (ISSN-L)
DOI
10.3390/rs8070594
OpenAlex
W2462592242
Cited by
1,152
References
4
FWCI
56.55
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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CoChat. (2026). Citation check: Pansharpening by Convolutional Neural Networks. https://app.cochat.ai/papers/10.3390/rs8070594
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Masi, G., Cozzolino, D., Verdoliva, L., & Scarpa, G. (2016). Pansharpening by Convolutional Neural Networks. Remote Sensing. https://doi.org/10.3390/rs8070594

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