OSC 2010: Optical Supercomputing pp 63-77 | Cite as

Compressive Sensing of Object-Signature

  • Dan E. Tamir
  • Natan T. Shaked
  • Wilhelmus J. Geerts
  • Shlomi Dolev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6748)

Abstract

Compressive sensing is a new framework for signal acquisition, compression, and processing. Of specific interest are two-dimensional signals such as images where an optical unit performs the acquisition and compression (i.e., compressive sensing or compressive imaging). The signal reconstruction and processing can be done by optical signal processing and/or digital signal processing. In this paper we review the theoretical basis of compressive sensing, present an optical implementation of image acquisition, and introduce a new application of compressive sensing where the actual signals used in the compressive sensing process are image object-signature (an object-signature is a specific representation of an object). We detail the application of compressive sensing to image object-signature and show the potential of compressive sensing to compress the data through analysis of several methods for obtaining signature and evaluation of the rate/distortions results of different compression methods including compressive sensing applied to object-signature.

Keywords

Digital Signal Processing Compressive Sampling Compressive Sensing Compressive Imaging Optical Super Computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dan E. Tamir
    • 1
  • Natan T. Shaked
    • 2
  • Wilhelmus J. Geerts
    • 3
  • Shlomi Dolev
    • 4
  1. 1.Department of Computer ScienceTexas State UniversitySan MarcosUSA
  2. 2.Department of Electrical and Computer EngineeringBen-Gurion University of the NegevBeer-ShevaIsrael
  3. 3.Department of PhysicsTexas State UniversitySan MarcosUSA
  4. 4.Department of Computer ScienceBen-Gurion University of the NegevBeer-ShevaIsrael

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