By Topic

Reducing the effects of quantization error in image compression systems: estimation of wavelet reconstruction filters using the LMS algorithm

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)
Prager, K.E. ; Hughes Aircraft Co., El Segundo, CA, USA ; Singer, P.F.

The results of an investigation into the use of the least mean square (LMS) algorithm as a tool for the estimating the proper reconstruction filters in a wavelet-based compression system are reported. The LMS algorithm is used to determine the inverse model of the process responsible for creating the correlated noise. The LMS coefficients describing this inverse model can be stored along with the compressed data. Upon reconstruction, these coefficients can be preconvolved with the wavelet filter pair, g(n) and h(n), creating a new filter pair, g'(n ) and h'(n). When this new filter pair is used to reconstruct the compressed signal, the effects of distortions are reduced

Published in:

Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium

Date of Conference:

4-6 Oct 1992