By Topic

A review of vector quantization techniques

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
$31 $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)
Vasuki, A. ; Dept. of Electron. & Commun. Eng., Kumaraguru Coll. of Technol., Coimbatore ; Vanathi, P.T.

The fundamental principles of quantization and the two basic types of quantization techniques-scalar and vector-have been introduced. The concept of VQ, its salient features, design of code book, and advantages/disadvantages has been dealt with in detail. VQ is a data compression technique, producing a reconstruction with as small a distortion as possible. The quality of the reconstruction depends on the amount of data that is discarded. The performance of different classes of VQ techniques like structured and unstructured VQ, memory and memoryless VQ, the types of VQ under each of these categories have been discussed. This article has surveyed these to a certain extent, and much more remains if a detailed analysis is required

Published in:

Potentials, IEEE  (Volume:25 ,  Issue: 4 )