Compressive imaging for video representation and coding

Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk

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

166 Scopus citations

Abstract

Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for reconstruction and processing. In this paper, we propose algorithms and hardware to support a new theory of Compressive Imaging. Our approach is based on a new digital image/video camera that directly acquires random projections of the light field without first collecting the pixels/voxels. Our camera architecture employs a digital micromirror array to perform optical calculations of linear projections of an image onto pseudorandom binary patterns. Its hall-marks include the ability to obtain an image with a single detection element while measuring the image/video fewer times than the number of pixels/voxels; this can significantly reduce the computation required for video acquisition/encoding. Since our system relies on a single photon detector, it can also be adapted to image at wavelengths that are currently impossible with conventional CCD and CMOS imagers. We are currently testing a prototype design for the camera and include experimental results.

Original languageEnglish (US)
Title of host publication25th PCS Proceedings
Subtitle of host publicationPicture Coding Symposium 2006, PCS2006
Volume2006
StatePublished - Dec 1 2006
Event25th PCS: Picture Coding Symposium 2006, PCS2006 - Beijing, China
Duration: Apr 24 2006Apr 26 2006

Other

Other25th PCS: Picture Coding Symposium 2006, PCS2006
CountryChina
CityBeijing
Period4/24/064/26/06

Keywords

  • Camera
  • Compressive sensing
  • Imaging
  • Incoherent projections
  • Linear programming
  • Random matrices
  • Sparsity
  • Video

ASJC Scopus subject areas

  • Engineering(all)

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