Hyperspectral imaging allows the collection of both spectral and spatial information. This modality is naturally fitted for object and material identification or detection processes, and has encountered a large success in the agriculture and food industries to name a few.
In snapshot spectral imaging, the 3D cube of images is taken in one shot, with the advantage that dynamic scenes can be analyzed. The simplest way to make a hyperspectral camera is to put an array of wavelength filters on the detector and then integrate this detector with standard camera objectives. The technical challenge is to make arrays of N wavelength filters and repeat this sequence up to 100‘000 times across the detector array, where each individual filter is matched to the pixel size and can be as small as a few microns.
In this work, we generate the same effect with just one N wavelength filter array which is then multiplied and imaged optically onto the detector to achieve the same effective filter array. This was first outlined by Levoy and Hoystmeyer using microlens arrays in a light field camera (plenoptics 1.0). Instead of building our own light field camera we used an existing commercial camera, Lytro™ and used it as the engine for our telecentric hyperspectral camera. In addition, the tools to extract and rebuild the raw data from the Lytro™ camera were developed.
We demonstrate reconstructed hyperspectral images with 9 spectral channels and show how this can be increased to achieve 81 spectral channels in a single snapshot.
Ross P. Stanley, Amina Chebira, Alireza Ghasemi, and Andrea L. Dunbar, "Hyperspectral imaging using a commercial light-field camera (Conference Presentation)," Proc. SPIE 10110, Photonic Instrumentation Engineering IV, 1011013 (Presented at SPIE OPTO: February 02, 2017; Published: 28 April 2017); https://doi.org/10.1117/12.2253599.5393916892001.
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