Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution

Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution

This article considers the inverse problem under hyperspectral images (HSIs) denoising framework. Recently, it has been shown that deep learning is a promising approach to image denoising. However, deep learning to be effective usually needs a massive amount of training data. Moreover, in a practica...

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Bibliographic Details
Main Authors: Keivan Faghih Niresi, Chong-Yung Chi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Adam optimizer
convolutional neural network
deep image prior
Huber loss function
hyperspectral denoising
least favorable distribution
Online Access:https://ieeexplore.ieee.org/document/9813381/

Internet

https://ieeexplore.ieee.org/document/9813381/

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