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To reconstruct spectral signals from multi-channel observations, inparticular trichromatic RGBs, has recently emerged as a promising alternativeto traditional scanning-based spectral imager. It has been proven that thereconstruction accuracy relies heavily on the spectral response of the RGBcamera in use. To improve accuracy, data-driven algorithms have been proposedto retrieve the best response curves of existing RGB cameras, or even to designbrand new three-channel response curves. Instead, this paper explores thefilter-array based color imaging mechanism of existing RGB cameras, andproposes to design the IR-cut filter properly for improved spectral recovery,which stands out as an in-between solution with better trade-off betweenreconstruction accuracy and implementation complexity. We further propose adeep learning based spectral reconstruction method, which allows to recover theillumination spectrum as well. Experiment results with both synthetic and realimages under daylight illumination have shown the benefits of our IR-cut filtertuning method and our illumination-aware spectral reconstruction method.

Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB