Deep Sparse and Low-Rank Prior for Hyperspectral Image Denoising
Author:
Affiliation:
1. University of Iceland,Faculty of Electrical and Computer Engineering,Reykjavik,Iceland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9883023/9883024/09884071.pdf?arnumber=9884071
Reference11 articles.
1. HYPERSPECTRAL IMAGE DENOISING WITH CUBIC TOTAL VARIATION MODEL
2. Weighted Nuclear Norm Minimization with Application to Image Denoising
3. Deep hyperspec-tral prior: Single-image denoising, inpainting, super-resolution;sidorov;Proc IEEE Conf Comput Vis Pattern Recognit,2019
4. Hyperspec-tral image denoising via noise-adjusted iterative low-rank matrix approximation;he;IEEE Trans Geosci Re-mote Sens,2015
5. Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural Networks
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1. A Hierarchical Low-Rank Denoising Model for Remote Sensing Images Based on Deep Unfolding;Sensors;2024-07-15
2. Multiscale reweighted smoothing regularization in curvelet domain for hyperspectral image denoising;International Journal of Remote Sensing;2024-06-05
3. A Denoising Network Based on Frequency-Spectral- Spatial-Feature for Hyperspectral Image;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023
4. Piecewise Weighted Smoothing Regularization in Tight Framelet Domain for Hyperspectral Image Restoration;IEEE Access;2023
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