By Topic

Speech and image signal compression with wavelets

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
W. Kinsner ; Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada ; A. Langi

The authors consider time-frequency multiresolution analysis based on wavelets, as it applies to speech/audio and image/video signal compression. They compare the wavelet analysis to the traditional short-window techniques used in signal compression. The performance of the discrete wavelet transform in terms of the bit rates and signal quality is comparable to that for other techniques such as the discrete cosine transform (DCT) for images and code-excited linear predictive coding (CELP) for speech, but with much less computational burden. Experiments with an image and Daubechies's four-coefficient wavelet show that truncation of wavelet coefficients as high as 90% still produces 30-dB peak signal-to-noise ratio (PSNR) quality. This is better than DCT. In an experiment on a male spoken sentence, the scheme reaches a 12.82-dB segmental signal-to-noise ratio (SEGSNR) at a rate of less than 4.8 kb/s. In comparison, the state-of-the-art CELP coding at 4.8 kbit/s can attain SEGSNR of 10-13 dB. Other experiments with images and Haar two-coefficient wavelet are also highlighted.

Published in:

WESCANEX 93. 'Communications, Computers and Power in the Modern Environment.' Conference Proceedings., IEEE

Date of Conference: