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Hyperspectral imaging is useful for applications ranging from medicaldiagnostics to agricultural crop monitoring; however, traditional scanninghyperspectral imagers are prohibitively slow and expensive for widespreadadoption. Snapshot techniques exist but are often confined to bulky benchtopsetups or have low spatio-spectral resolution. In this paper, we propose anovel, compact, and inexpensive computational camera for snapshot hyperspectralimaging. Our system consists of a tiled spectral filter array placed directlyon the image sensor and a diffuser placed close to the sensor. Each point inthe world maps to a unique pseudorandom pattern on the spectral filter array,which encodes multiplexed spatio-spectral information. By solving asparsity-constrained inverse problem, we recover the hyperspectral volume withsub-super-pixel resolution. Our hyperspectral imaging framework is flexible andcan be designed with contiguous or non-contiguous spectral filters that can bechosen for a given application. We provide theory for system design,demonstrate a prototype device, and present experimental results with highspatio-spectral resolution.

Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array