Geometric tools for image compression

Michael Wakin, Justin Romberg, Hyeokho Choi, Richard Baraniuk

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

5 Scopus citations

Abstract

Images typically contain strong geometric features, such as edges, that impose a structure on pixel values and wavelet coefficients. Modeling the joint coherent behavior of wavelet coefficients is difficult, and standard image coders fail to fully exploit this geometric regularity. We introduce wedgelets as a geometric tool for image compression. Wedgelets offer piecewise-linear approximations of edge contours and can be efficiently encoded. We describe the fundamental challenges that arise when applying such a tool to image compression. To meet these challenges, we also propose an efficient rate-distortion framework for natural image compression using wedgelets.

Original languageEnglish (US)
Title of host publicationConference Record of the Asilomar Conference on Signals, Systems and Computers
EditorsM.B. Matthews
Pages1725-1729
Number of pages5
Volume2
StatePublished - 2002
EventThe Thirty-Sixth Asilomar Conference on Signals Systems and Computers - Pacific Groove, CA, United States
Duration: Nov 3 2002Nov 6 2002

Other

OtherThe Thirty-Sixth Asilomar Conference on Signals Systems and Computers
CountryUnited States
CityPacific Groove, CA
Period11/3/0211/6/02

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Hardware and Architecture

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