Access Restriction

Author Ferens, K. ♦ Kinsner, W.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1995
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Multiple signal classification ♦ Wavelet transforms ♦ Psychoacoustic models ♦ Wideband ♦ Frequency ♦ Fourier transforms ♦ Signal resolution ♦ Data compression ♦ Wavelet domain ♦ Fractals
Abstract This paper describes modelling of the coefficient domain in wavelet subbands of wideband audio signals for low-bit rate and high-quality compression. The purpose is to develop models of the perception of wideband audio signals in the wavelet domain. The coefficients in the wavelet subbands are quantized using a scheme that adapts to the subband signal by setting the quantization step size for a particular subband to a size that is inversely proportional to the subband energy, and then, within a subband, by modifying the energy determined step size as inversely proportional to the amplitude probability density of the coefficient. The amplitude probability density of the coefficients in each subband is modelled using learned vector/scalar quantization employing frequency sensitive competitive learning. The source data consists of 1-channel, 16-bit linear data sampled at 44.1 kHz from a CD containing major classical and pop music. Preliminary results show a bit-rate of 150 kbps, rather than 705.6 kbps, with no perceptual loss in quality. The wavelet transform provides better results for representing multifractal signals, such as wide band audio, than do other standard transforms, such as the Fourier transform.
Description Author affiliation: Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada (Ferens, K.; Kinsner, W.)
ISBN 0818670126
ISSN 10680314
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1995-03-28
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 74.50 kB

Source: IEEE Xplore Digital Library