Cart (Loading....) | Create Account
Close category search window
 

Successive approximation quantization for image compression

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

3 Author(s)
da Silva, E.A.B. ; COPPE, Univ. Fed. do Rio de Janeiro, Brazil ; Fonini, D.A., Jr. ; Craizer, M.

Successive approximation (SA) quantization is part of many of the state-of-the-art image and video compression methods. We first make a review of it, starting from the classical optimality considerations of Equitz and Cover(1991) and then proceed to Mallat and Falzon (see IEEE Transactions on Signal Processing, vol.46, no.4, 1998) results concerning low bit-rate transform coding. We then develop a general theory of SA quantization which we refer to as o-expansions. This theory explains the published results obtained by both scalar and vector SA quantization methods, and indicates how further performance improvements can be obtained.

Published in:

Circuits and Systems Magazine, IEEE  (Volume:2 ,  Issue: 3 )

Date of Publication:

Third Quarter 2002

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.