Scalable information-optimal compressive imager: Target recognition task

Ronan Kerviche, Amit Ashok

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

Abstract

We present a scalable compressive imager that employs information-optimal measurements capable of detecting and classifying two or more targets in natural backgrounds. Measurements are optimized using Cauchy-Schwarz mutual information that bounds the probability of error.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2016
PublisherOSA - The Optical Society
ISBN (Print)9781943580156
DOIs
StatePublished - Jul 18 2016
EventComputational Optical Sensing and Imaging, COSI 2016 - Heidelberg, Germany
Duration: Jul 25 2016Jul 28 2016

Other

OtherComputational Optical Sensing and Imaging, COSI 2016
CountryGermany
CityHeidelberg
Period7/25/167/28/16

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint Dive into the research topics of 'Scalable information-optimal compressive imager: Target recognition task'. Together they form a unique fingerprint.

  • Cite this

    Kerviche, R., & Ashok, A. (2016). Scalable information-optimal compressive imager: Target recognition task. In Computational Optical Sensing and Imaging, COSI 2016 OSA - The Optical Society. https://doi.org/10.1364/COSI.2016.CW5D.7