A comparative study of image compression based on directional wavelets

Kun Li, Wenli Xu, Qionghai Dai, Yao Wang

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


Discrete wavelet transform is an effective tool to generate scalable stream, but it cannot efficiently represent edges which are not aligned in horizontal or vertical directions, while natural images often contain rich edges and textures of this kind. Hence, recently, intensive research has been focused particularly on the directional wavelets which can effectively represent directional attributes of images. Specifically, there are two categories of directional wavelets: redundant wavelets (RW) and adaptive directional wavelets (ADW). One representative redundant wavelet is the dual-tree discrete wavelet transform (DDWT), while adaptive directional wavelets can be further categorized into two types: with or without side information. In this paper, we briefly introduce directional wavelets and compare their directional bases and image compression performances.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visual Communications and Image Processing 2007
EditionPART 2
ISBN (Print)0819466212, 9780819466211
StatePublished - 2007
EventVisual Communications and Image Processing 2007 - San Jose, CA, United States
Duration: Jan 30 2007Feb 1 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
NumberPART 2
ISSN (Print)0277-786X


OtherVisual Communications and Image Processing 2007
Country/TerritoryUnited States
CitySan Jose, CA


  • Adaptive directional wavelets
  • Basis functions
  • Compression performances
  • Context-based arithmetic coding
  • Directional wavelets
  • Discrete wavelet transform
  • Dual-tree discrete wavelet transform
  • Redundant wavelets
  • Scalable image coding
  • Side information

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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