Piecewise Weighted Smoothing Regularization in Tight Framelet Domain for Hyperspectral Image Restoration
Author:
Affiliation:
1. School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China
2. School of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Funder
Scientifific Research Project of Colleges from Liaoning Department of Education
National Key Research and Development Program of China
Discipline Innovation Team of Liaoning Technical University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10005085.pdf?arnumber=10005085
Reference50 articles.
1. Deep Hyperspectral Prior: Single-Image Denoising, Inpainting, Super-Resolution
2. Hider: A Hyperspectral Image Denoising Transformer With Spatial–Spectral Constraints for Hybrid Noise Removal
3. Hyperspectral Image Mixed Noise Removal Using Subspace Representation and Deep CNN Image Prior
4. Hyperspectral Imagery Denoising by Deep Learning With Trainable Nonlinearity Function
5. Hyperspectral Denoising Using Unsupervised Disentangled Spatiospectral Deep Priors
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1. Multiscale reweighted smoothing regularization in curvelet domain for hyperspectral image denoising;International Journal of Remote Sensing;2024-06-05
2. Image Resolution on Multiple Parameters using Spatial and Transform Domain: A Systematic Analysis;2023 International Conference on Disruptive Technologies (ICDT);2023-05-11
3. A Noise Estimation Method for Hyperspectral Image Based on Stacked Autoencoder;IEEE Access;2023
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