Compressive Classification via Secant Projections

Yun Li; Chinmay Hegde; Richard G. Baraniuk; Kevin F. Kelly

doi:10.1364/COSI.2013.CTu1C.3

Imaging and Applied Optics
OSA Technical Digest (online) (Optica Publishing Group, 2013),
paper CTu1C.3
•https://doi.org/10.1364/COSI.2013.CTu1C.3

Compressive Classification via Secant Projections

Yun Li, Chinmay Hegde, Richard G. Baraniuk, and Kevin F. Kelly

Computational Optical Sensing and Imaging 2013

Arlington, Virginia United States
23–27 June 2013
ISBN: 978-1-55752-975-6

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Structured Illumination and Single-pixel Imaging (CTu1C)

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Y. Li, C. Hegde, R. G. Baraniuk, and K. F. Kelly, "Compressive Classification via Secant Projections," in Imaging and Applied Optics, OSA Technical Digest (online) (Optica Publishing Group, 2013), paper CTu1C.3.

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Abstract

One novel dimensional reduction method based on manifold modeling is applied on Rice single pixel camera for targets classification. The number of measurements is at least halved compared with equivalent classification result via random projections.

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