Computational Spectral Imaging with Photon Sieves

Date

2016-01-01

Author

Öktem, Sevinç Figen
Davila, Joseph M.

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Spectral imaging, the sensing of spatial information as a function of wavelength, is a widely used diagnostic technique in diverse fields such as physics, chemistry, biology, medicine, astronomy, and remote sensing. In this paper, we present a novel computational imaging modality that enables high-resolution spectral imaging by distributing the imaging task between a photon sieve system and a computer. The photon sieve system, coupled with a moving detector, provides measurements from multiple planes. Then an inverse problem is solved in a Bayesian estimation framework to reconstruct the multi-spectral images from these superimposed and blurred measurements. The results illustrate that this technique enables higher spatial and spectral resolution than conventional filtered-based spectral imagers.

Subject Keywords

Spectral imaging , Remote sensing, Image formation, Computational imaging, Inverse problems

URI

https://hdl.handle.net/11511/40476

DOI

https://doi.org/10.1109/siu.2016.7495768

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Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

S. F. Öktem and J. M. Davila, “Computational Spectral Imaging with Photon Sieves,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40476.