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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 42, Iss. 17 — Jun. 10, 2003
  • pp: 3379–3389

Feature-specific imaging

Mark A. Neifeld and Premchandra Shankar  »View Author Affiliations


Applied Optics, Vol. 42, Issue 17, pp. 3379-3389 (2003)
http://dx.doi.org/10.1364/AO.42.003379


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Abstract

We analyze the performance of feature-specific imaging systems. We study incoherent optical systems that directly measure linear projects of the optical irradiance distribution. Direct feature measurement exploits the multiplex advantage, and for small numbers of projections can provide higher feature-fidelity than those systems that postprocess a conventional image. We examine feature-specific imaging using Wavelet, Karhunen-Loeve (KL), Hadamard, and independent-component features, quantifying feature fidelity in Gaussian-, shot-, and quantization-noise environments. An example of feature-specific imaging based on KL projections is analyzed and demonstrates that within a high-noise environment it is possible to improve image fidelity via direct feature measurement. A candidate optical system is presented and a preliminary implementational study is undertaken.

© 2003 Optical Society of America

OCIS Codes
(100.3010) Image processing : Image reconstruction techniques
(100.5010) Image processing : Pattern recognition
(110.0110) Imaging systems : Imaging systems
(110.6980) Imaging systems : Transforms
(200.4740) Optics in computing : Optical processing

Citation
Mark A. Neifeld and Premchandra Shankar, "Feature-Specific Imaging," Appl. Opt. 42, 3379-3389 (2003)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-42-17-3379

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