Wavelet transform coding using NIVQ

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations


Discrete wavelet transform is an ideal tool for multi-resolution representation of image signals. Some promising results have been recently reported on the application of wavelet transform for image compression. In this paper, we propose a new wavelet coding technique for image compression. The proposed scheme has the advantages of improved coding performance and reduced computational complexity. The input image is first decomposed into a pyramid structure with three layers using 2-D wavelet transform. A block size of 2m - 3 (m=1, 2, 3) is used for each orientation sub-image at the m-th layer to form 64-D vectors by combining the corresponding blocks in all the sub-images. The 64-D vectors are then encoded using 16-D non-linear interpolative vector quantization (NIVQ). At the decoder, the indices are used to reconstrucL the 64-D vectors directly from a 64-D codebook designed using a non-linear interpolative technIue. The proposed scheme not only exploits the correlation among the wavelet sub-images but also preserves the high frequency sub-images. Simulation results show that the reconstructed image of a superior quality can be obtained at a compression ratio of about 100:1.

Original languageEnglish (US)
Pages (from-to)999-1009
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1993
Externally publishedYes
EventVisual Communications and Image Processing 1993 - Cambridge, MA, United States
Duration: Nov 7 1993Nov 7 1993

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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