Adaptive feature-specific imaging

Mark A. Neifeld, Pawan K. Bahetic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Feature-specific imaging (FSI) is a method by which non-traditional projections of object space may be computed directly in the optical domain. The resulting feature-specific measurements provide the advantages of reduced hardware complexity and improved measurement SNR. This SNR advantage translates into improved task (e.g., target recognition and/or tracking) performance. Adaptive FSI refers to any FSI system for which the results of previous measurements are used to determine future measurement basis vectors. This paper will describe an adaptive FSI system based on the sequential hypothesis testing approach. We will quantify the benefits of adaptation for a M-class recognition task, and present an extension of the AFSI system to incorporate null hypothesis.

Original languageEnglish (US)
Title of host publicationAdaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems
DOIs
StatePublished - 2009
EventAdaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems - San Diego, CA, United States
Duration: Aug 2 2009Aug 3 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7468
ISSN (Print)0277-786X

Other

OtherAdaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems
Country/TerritoryUnited States
CitySan Diego, CA
Period8/2/098/3/09

Keywords

  • Feature-specific imaging
  • Image recognition
  • Sequential hypothesis testing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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