Paper
23 September 2014 Reconstruction algorithms for compressive hyperspectral imaging systems with separable spatial and spectral operators
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Abstract
Recently we introduced a hyperspectral compressive sensing scheme that uses separable projections in the spatial and spectral domains. The separable encoding schemes facilitates the optical implementation, reduces the computational burden dramatically, and storage requirements. Owing to these benefits we have been able to encode the hyperspectral cube in all three dimensions. In this work we present a comparison between various reconstructions methods applied to the hyperspectral data captured with our separable compressive sensing systems.
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Yaniv Oiknine, Yitzhak August, and Adrian Stern "Reconstruction algorithms for compressive hyperspectral imaging systems with separable spatial and spectral operators", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921703 (23 September 2014); https://doi.org/10.1117/12.2064640
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Cited by 2 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Imaging systems

Hyperspectral imaging

Compressed sensing

MATLAB

Multiplexing

Sensing systems

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