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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Autors principals:	Keivan Faghih Niresi, Chong-Yung Chi
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2022-01-01
Col·lecció:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Matèries:	Adam optimizer convolutional neural network deep image prior Huber loss function hyperspectral denoising least favorable distribution
Accés en línia:	https://ieeexplore.ieee.org/document/9813381/
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