Hence improvements in hyperspectral imagers and cameras are essential towards progression in visible light spectroscopy. Various algorithms have been proposed for reconstructing sample spectrum from hyperspectral images which take advantage of spatial-spectral information 13, 14, 15, 16, 17, 18, 19, 20, 21. Visible light spectroscopy when used in imaging modality rather than spot spectroscopy allows computational algorithms to take advantage of spatial-spectral information such as spectral similarity in neighboring spatial pixels. Such imaging systems are called hyperspectral cameras which has many widespread usages. Hence cameras with many color channels are often used for spectroscopy. Conventional RGB camera can provide only 3 color information, which is often insufficient to detect sharp features in spectrum. Visible Light Spectroscopy has many applications including cancer detection 1, 2, 3, remote sensing 4, 5, 6, mineralogy 7, food safety 8 and artwork authentication and preservation 9, 10, 11, 12.
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