GASTINEAU, Anais; AUJOL, Jean-Francois; BERTHOUMIEU, Yannick; GERMAIN, Christian

doi:10.1109/tgrs.2021.3060958

Institut de Mathématiques de Bordeaux [IMB]

AUJOL, Jean-Francois

Institut de Mathématiques de Bordeaux [IMB]

BERTHOUMIEU, Yannick
Laboratoire de l'intégration, du matériau au système [IMS]

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Article de revue

Ce document a été publié dans

IEEE Transactions on Geoscience and Remote Sensing. 2022-01, vol. 60, p. 1-11

Résumé en anglais

The pansharpening problem amounts to fusing a high-resolution panchromatic image with a low-resolution multispectral image so as to obtain a high-resolution multispectral image. Therefore, the preservation of the spatial resolution of the panchromatic image and the spectral resolution of the multispectral image is of key importance for the pansharpening problem. To cope with it, we propose a new method based on a bidiscriminator in a generative adversarial network (GAN) framework. The first discriminator is optimized to preserve textures of images by taking as input the luminance and the near-infrared band of images, and the second discriminator preserves the color by comparing the chroma components Cb and Cr. Thus, this method allows to train two discriminators, each one with a different and complementary task. Moreover, to enhance these aspects, the proposed method based on bidiscriminator, and called MDSSC-GAN SAM, considers a spatial and a spectral constraint in the loss function of the generator. We show the advantages of this new method on experiments carried out on Pléiades and World View 3 satellite images.< Réduire

Mots clés en anglais

Bidiscriminator

deep learning

generative adversarial network (GAN)

pansharpening

remote sensing

URI

https://oskar-bordeaux.fr/handle/20.500.12278/140368

DOI

http://dx.doi.org/10.1109/tgrs.2021.3060958

Project ANR

Super-résolution d'images multi-échelles en sciences des matériaux avec des attributs géométriques - ANR-18-CE92-0050

Unités de recherche

IMS : Laboratoire de l'Intégration du Matériau au Système - UMR 5218

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Generative Adversarial Network for Pansharpening With Spectral and Spatial Discriminators