Joint Reconstruction and Pansharpening for High-Resolution Hyperspectral Single-Pixel Imaging

We address the problem of single-pixel hyperspectral imaging, which requires balancing acquisition speed and spatial resolution. To improve spatial resolution when acquiring a small number of measurements in low-light conditions, we leverage side information from a high-resolution grayscale camera. Our joint reconstruction and fusion approach combines hyperspectral measurements and the grayscale image by minimizing a hand-crafted cost function that incorporates smooth spatial regularization and a low-rank approximation. Experiments on synthetic data show that our method improves spatial fidelity and per-pixel accuracy in photon-limited settings while preserving spectral alignment.