5 citations · 5 across the 4 of their papers we have counts for
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Interpretable Hyperspectral Unmixing Framework with Fixed Endmember Prior and Structured Residual Refinement
Ziyi Guan, Jianping Zhang, Qian Liu
Hyperspectral unmixing decomposes mixed pixels into material endmembers and their abundances from contiguous spectral observations. In modular sensing pipelines, endmembers are oft…
AXS-Net: Interpretable Deep Unfolding for Hyperspectral Image Denoising via Spectral Basis Unmixing and Structured Noise Refinement
Ziyi Guan, Jianping Zhang, Zheng Yang
Hyperspectral images (HSIs) are often degraded by mixed noise, including band-dependent Gaussian perturbations and structured artifacts such as stripes, dead-lines, and impulse noi…
A Dual-domain Refinement Network with FBP-based Jacobian Learning for Sparse-view Dual-Energy CT Material Decomposition
Qian Liu, Xiaohong Fan, Ke Chen +3
Dual-energy CT (DECT) exploits attenuation differences across different X-ray spectra to provide richer material information and has been widely used in medical imaging. While spar…
A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing
Yujie Feng, Yin Yang, Xiaohong Fan +3
Recently, deep learning methods have gained remarkable achievements in the field of image restoration for remote sensing (RS). However, most existing RS image restoration methods f…
PRISTA-Net: Deep Iterative Shrinkage Thresholding Network for Coded Diffraction Patterns Phase Retrieval
Aoxu Liu, Xiaohong Fan, Yin Yang +1
The problem of phase retrieval (PR) involves recovering an unknown image from limited amplitude measurement data and is a challenge nonlinear inverse problem in computational imagi…
A Multi-scale Generalized Shrinkage Threshold Network for Image Blind Deblurring in Remote Sensing
Yujie Feng, Yin Yang, Xiaohong Fan +2
Remote sensing images are essential for many applications of the earth's sciences, but their quality can usually be degraded due to limitations in sensor technology and complex ima…