By Topic

Vector quantization for image compression based on fuzzy clustering

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

4 Author(s)
Boudraa, A.-O. ; Inst. Galilee, Univ. de Paris-Nord, Villetaneuse, France ; Kanafani, Q. ; Beghdadi, A. ; Zergainoh, A.

In this paper a codebook design for image compression based on the fuzzy c-means (FCM) algorithm is presented. The codebook design from training vectors is viewed as a fuzzy clustering problem of unlabeled data points into clusters. Due to computational cost of FCM to generate the codebook, a fast version (FFCM), which operates on the image histogram, is used to obtain a good initial codebook to start the FCM algorithm. Experimental results are presented to illustrate the performance of the proposed compression method

Published in:

Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on  (Volume:2 )

Date of Conference:

1999