Remote Sensing Image Pansharpening Feedback Network Based on Perceptual Loss

Pansharpening aims to sharpen a low-resolution multi-channel multispectral(MS) image from a high-resolution single-channel panchromatic(PAN) image to obtain a high resolution multispectral(HRMS) image,which is an important task in remote sensing image processing.A feedback network based on perceptual loss is proposed.First,the detail information and the spectral information are extracted from the PAN image and the MS image respectively,and then they are combined to use the stacked up-and down-sampling layers and dense connections for information fusion.The feedback connection is used to enrich the low-level information with high-level information.Finally,the HRMS image is reconstructed.Compared with the traditional pansharpening algorithms,the proposed algorithm uses the PAN image and the HRMS image as the supervision of the network,and the output image contains richer spatial detail information by obtaining the perceptual loss of the PAN image and the network reconstructed HRMS image.The experimental results show that the proposed algorithm has better results than the widely used algorithms both in objective evaluation and visual perception.

Abstract licence: CC BY-NC-ND

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