This paper introduces a computational framework for recovering spectral information from single-shot photos using a specially designed color chart and algorithm, achieving spectral resolution comparable to scientific spectrometers. It eliminates the need for training data or pre-trained models and has potential applications in accessible optical spectroscopy and hyperspectral imaging.
This article details how Living Optics' hyperspectral imaging technology can be used to non-destructively measure grape sugar levels for optimized harvest timing, improving wine quality and reducing financial risk. It outlines lab and field testing demonstrating the correlation between hyperspectral data and Brix values.
