Xiang Li

Conjugate Gradient Unrolled Network with PSF Conditioning for Non-Diagonal Data Fidelity in CASSI Reconstruction

A deep unfolding framework is proposed that addresses this fundamental algorithmic challenge through three contributions: a learned gradient refinement module with wavelength-adaptive step sizes generated from a per-wavelength PSF embedding, a PSF-conditioned penalty estimator, and a Monte Carlo PSF training strategy that improves robustness to manufacturing-induced PSF variations.