AI RESEARCH
LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imaging
arXiv CS.CV
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ArXi:2511.18513v2 Announce Type: replace Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruction. Existing DUNs are derived from full-HSI imaging models, where each stage operates directly on the high-dimensional HSI, refining the entire data cube based on the single 2D coded measurement. However, this paradigm leads to computational redundancy and suffers from the ill-posed nature of mapping 2D residuals back to 3D space of