CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing

CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing

Deep learning based methods hold state-of-the-art results in low-level image processing tasks, but remain difficult to interpret due to their black-box construction. Unrolled optimization networks present an interpretable alternative to constructing deep neural networks by deriving their architectur...

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Bibliographic Details
Main Authors: Nikola Janjusevic, Amirhossein Khalilian-Gourtani, Yao Wang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Interpretable deep learning
unrolled networks
blind denoising
joint demosaicing and denoising
dictionary learning
sparse coding
Online Access:https://ieeexplore.ieee.org/document/9769957/

Internet

https://ieeexplore.ieee.org/document/9769957/

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