Compressive ultraspectral imaging using multiscale structured illumination

Vladislav Kravets; Paul Kondrashov; Adrian Stern

doi:10.1364/AO.58.000F32

Compressive ultraspectral imaging using multiscale structured illumination

Vladislav Kravets, Paul Kondrashov, Adrian Stern

Unit of Photonics and Electro-Optics Engineering

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We present a novel compressive spectral imaging technique that attains spatially resolved ultraspectral resolution. The technique employs a multiscale sampling technique based on the Hadamard basis for the single pixel hyperspectral imager. The proposed multiscale sampling method offers high-quality images at a low compression ratio while also facilitating a preview image at a lower resolution by using the fast Hadamard transform.

Original language	English
Pages (from-to)	F32-F39
Journal	Applied Optics
Volume	58
Issue number	22
DOIs	https://doi.org/10.1364/AO.58.000F32
State	Published - 1 Aug 2019

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Engineering (miscellaneous)
Electrical and Electronic Engineering

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10.1364/AO.58.000F32

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title = "Compressive ultraspectral imaging using multiscale structured illumination",

abstract = "We present a novel compressive spectral imaging technique that attains spatially resolved ultraspectral resolution. The technique employs a multiscale sampling technique based on the Hadamard basis for the single pixel hyperspectral imager. The proposed multiscale sampling method offers high-quality images at a low compression ratio while also facilitating a preview image at a lower resolution by using the fast Hadamard transform.",

author = "Vladislav Kravets and Paul Kondrashov and Adrian Stern",

note = "Funding Information: Acknowledgment. Vladislav Kravets would like to thank the Kreitman Foundation for supporting his research. Funding Information: Ministry of Science, Technology and Space (3-18410). Vladislav Kravets would like to thank the Kreitman Foundation for supporting his research. Publisher Copyright: {\textcopyright} 2019 Optical Society of America",

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doi = "10.1364/AO.58.000F32",

language = "English",

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T1 - Compressive ultraspectral imaging using multiscale structured illumination

AU - Kravets, Vladislav

AU - Kondrashov, Paul

AU - Stern, Adrian

N1 - Funding Information: Acknowledgment. Vladislav Kravets would like to thank the Kreitman Foundation for supporting his research. Funding Information: Ministry of Science, Technology and Space (3-18410). Vladislav Kravets would like to thank the Kreitman Foundation for supporting his research. Publisher Copyright: © 2019 Optical Society of America

PY - 2019/8/1

Y1 - 2019/8/1

N2 - We present a novel compressive spectral imaging technique that attains spatially resolved ultraspectral resolution. The technique employs a multiscale sampling technique based on the Hadamard basis for the single pixel hyperspectral imager. The proposed multiscale sampling method offers high-quality images at a low compression ratio while also facilitating a preview image at a lower resolution by using the fast Hadamard transform.

AB - We present a novel compressive spectral imaging technique that attains spatially resolved ultraspectral resolution. The technique employs a multiscale sampling technique based on the Hadamard basis for the single pixel hyperspectral imager. The proposed multiscale sampling method offers high-quality images at a low compression ratio while also facilitating a preview image at a lower resolution by using the fast Hadamard transform.

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U2 - 10.1364/AO.58.000F32

DO - 10.1364/AO.58.000F32

M3 - Article

AN - SCOPUS:85072022608

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VL - 58

SP - F32-F39

JO - Applied Optics

JF - Applied Optics

IS - 22

ER -

Compressive ultraspectral imaging using multiscale structured illumination

Abstract

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