Quantization of wavelet coefficients for image compression

Aziz Mohammed, Khalid Sayood

Research output: Contribution to journalConference articlepeer-review


The use of wavelets and multiresolution analysis is becoming increasingly popular for image compression. In this paper we examine several different approaches to the quantization of wavelet coefficients. A standard approach in subband coding is to use DPCM to encode the lowest band while the higher bands are quantized using a scalar quantizer for each band or a vector quantizer. We implement these schemes using a variety of quantizer including pdf optimized quantizers and recursively indexed scalar quantizers (RISQ). We then incorporate a threshold operation to prevent the removal of perceptually important information. We show that there is a both subjective and objective improvements in performance when we use the RISQ and the perceptual thresholds. The objective performance measure shows a consistent two to three dB improvement over a wide range of rates. Finally we use a recursively indexed vector quantizer (RIVQ) to encode the wavelet coefficients. The RIVQ can operate at relatively high rates and is therefore particularly suited for quantizing the coefficients in the lowest band.

Original languageEnglish (US)
Pages (from-to)483
Number of pages1
JournalData Compression Conference Proceedings
StatePublished - 1995
EventProceedings of the 5th Data Compression Conference - Snowbird, UT, USA
Duration: Mar 28 1995Mar 30 1995

ASJC Scopus subject areas

  • Computer Networks and Communications


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