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cs.CV2026
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…
cs.CV2026
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…
cs.CV2026
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…