By Topic

Reducing computation for vector quantization by using bit-mapped look-up table

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

5 Author(s)
Rong-Chang Chen ; Dept. of Logistics Eng. & Manage., Nat. Taichung Inst. of Technol., Taiwan ; Chia-Tai Chan ; Pi-Chung Wang ; Tung-Shou Chen
more authors

Vector quantization (VQ) is an elementary technique for image compression. However, searching for the nearest codeword in a codebook is time-consuming. In this work, we propose an adaptive scheme "bit-mapped look-up table" (BLUT) which can prune codewords rapidly. This new scheme uses positional information to represent the geometric relation within codewords. Accordingly, the lookup procedure could refer the information to sift candidate codewords easily. This scheme might also cooperate with existing schemes to speed-up searching. Simulation results confirm this effectiveness.

Published in:

Networking, Sensing and Control, 2004 IEEE International Conference on  (Volume:2 )

Date of Conference: