Image coding using wavelet transform and classified vector quantisation

E. Lin, Salari

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The wavelet transform, which provides a multiresolution representation of images, has been widely used in image compression. A new image coding scheme using the wavelet transform and classified vector quantisation is presented. The input image is first decomposed into a hierarchy of three layers containing ten subimages by the discrete wavelet transform. The lowest resolution low frequency subimage is scalar quantised with 8 bits/pixel. The high frequency subimages are compressed by classified vector quantisation to utilise the crosscorrelation among different resolutions while reducing the edge distortion and computational complexity. Vectors are constructed by combining the corresponding wavelet coefficients of different resolutions in the , same orientation and classified according to the magnitude and the position of wavelet transform coefficients. Simulation results show that the proposed scheme has a better performance than those utilising current scalar or vector quantisation schemes.

Original languageEnglish
Pages (from-to)285-291
Number of pages7
JournalIEE Proceedings: Vision, Image and Signal Processing
Volume143
Issue number5
DOIs
StatePublished - 1996

Keywords

  • Classified vector quantisation
  • Image processing
  • Wavelet transform

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