By Topic

Adaptive quantization without side information using scalar-vector quantization and trellis coded quantization

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)
Yoo, Y. ; Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA ; Ortega, A.

We combine backward adaptive quantization with the scalar-vector quantizer (SVQ) and the trellis coded quantizer (TCQ) both of which have an underlying scalar quantizer (USQ) in their structure. The resulting adaptive scalar-vector quantizer (ASVQ) and adaptive trellis coded quantizer (ATCQ) redesign the USQ based on the past quantized outputs. The adaptive quantizers require no side information and also outperform the SVQ and the TCQ, respectively, when the input signal is non-stationary. For an input sequence from a bimodal source switching infrequently between two Gaussian distributions with the same mean and different variances, both adaptive quantizers achieve performance gains of more than 1.3 dB over the non-adaptive quantizers designed on the training set from the same bimodal source. Also the adaptive quantizers demonstrate minimal performance degradation due to adaptation when stationary inputs are considered.

Published in:

Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference on  (Volume:2 )

Date of Conference:

Oct. 30 1995-Nov. 1 1995