A Residual Dense Generative Adversarial Network For Pansharpening With Geometrical Constraints

Anais GASTINEAU, Jean-Francois AUJOL, Yannick BERTHOUMIEU, Christian GERMAIN
2020 2020 IEEE International Conference on Image Processing (ICIP)  
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, an
more » ... tant point for the pansharpening problem is to preserve the geometry of the image. Hence, we propose to add a regularization term in the loss function of the generator: it preserves the geometry of the target image so that a better solution is obtained. In addition, we propose geometrical measures that illustrate the advantages of this new method.
doi:10.1109/icip40778.2020.9191230 dblp:conf/icip/GastineauABG20 fatcat:nbtoluoblvdspatiur5da6kdde