PercepPan: Towards Unsupervised Pan-Sharpening Based on Perceptual Loss

PercepPan: Towards Unsupervised Pan-Sharpening Based on Perceptual Loss

In the literature of pan-sharpening based on neural networks, high resolution multispectral images as ground-truth labels generally are unavailable. To tackle the issue, a common method is to degrade original images into a lower resolution space for supervised training under the Wald’s protocol. In...

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Bibliographic Details
Main Authors: Changsheng Zhou, Jiangshe Zhang, Junmin Liu, Chunxia Zhang, Rongrong Fei, Shuang Xu
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Remote Sensing
Subjects:
pan-sharpening
perceptual loss
auto-encoder
generative adversarial networks
unsupervised learning
Online Access:https://www.mdpi.com/2072-4292/12/14/2318

Internet

https://www.mdpi.com/2072-4292/12/14/2318

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