Bayesian Pan-Sharpening With Multiorder Gradient-Based Deep Network Constraints

Bayesian Pan-Sharpening With Multiorder Gradient-Based Deep Network Constraints

Pan-sharpening aims at acquiring a multispectral image with a high spatial resolution by fusing a low-resolution multispectral image and a panchromatic image. In order to improve spatial details and reduce spectral distortions, we develop a new pan-sharpening model based on the Bayesian theory, whic...

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Bibliographic Details
Main Authors: Penghao Guo, Peixian Zhuang, Yecai Guo
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Bayesian theory
convolutional neural network (CNN)
multiorder gradient
pan-sharpening
Online Access:https://ieeexplore.ieee.org/document/9020056/

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