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The pansharpening problem consists in fusing a high resolution panchromatic image with a low resolution multispectral image in order to obtain a high resolution multispectral image. In this paper, we adapt a Residual Dense architecture for the generator in a Generative Adversarial Network framework. Indeed, this type of architecture avoids the vanishing gradient problem faced when training a network by re-injecting previous information thanks to dense and residual connections. Moreover, andoi:10.1109/icip40778.2020.9191230 dblp:conf/icip/GastineauABG20 fatcat:nbtoluoblvdspatiur5da6kdde