Distributed image compression for sensor networks using correspondence analysis and super-resolution

Raymond Wagner, Robert Nowak, Richard Baraniuk

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

83 Scopus citations

Abstract

We outline a distributed coding technique for images captured from sensors with overlapping fields of view in a sensor network. First, images from correlated views are roughly registered (relative to a sensor of primary interest) via a low-bandwidth data-sharing method involving image feature points and feature point correspondence. An area of overlap is then identified, and each sensor transmits a low-resolution version of the common image block to the receiver, amortizing the coding cost for that block among the set of sensors. Super-resolution techniques are finally employed at the receiver to reconstruct a high-resolution version of the common block. We discuss the registration and super-resolution techniques used and present examples of each step in the proposed coding process. A numerical analysis illustrating the potential coding benefit follows, and we conclude with a brief discussion of the key issues remaining to be resolved on the path to coder robustness.

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Pages597-600
Number of pages4
Volume1
StatePublished - Dec 16 2003
EventProceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain
Duration: Sep 14 2003Sep 17 2003

Other

OtherProceedings: 2003 International Conference on Image Processing, ICIP-2003
CountrySpain
CityBarcelona
Period9/14/039/17/03

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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