Parallel Approach to Fuzzy Vector Quantization for Image Compression

Huynh Van Luong, Yong-Min Kim, Byung-Kook Kim, Jong-Myon Kim, Cheol-Hong Kim

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Fuzzy clustering based vector quantization algorithm has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, we introduce a parallel implementation of Fuzzy Vector Quantization (FVQ) using a representative data parallel architecture which consists of 4,096 processing elements (PEs). Our parallel approach provides a computationally efficient solution with the 4,096 PEs by employing an effective vector assignment strategy for the transition from soft to crisp decisions during the clustering process. Experimental results show that our parallel approach provides 1000times greater performance and 100times higher energy efficiency than other implementations using commercial processors such as ARM families.
Original languageEnglish
Title of host publication10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09
PublisherIEEE
Publication date2009
Pages510-515
ISBN (Print)978-0-7695-3642-2
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing (SNPD 2009) - Daegu, Korea, Republic of
Duration: 27 May 200929 May 2009

Conference

Conference10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing (SNPD 2009)
CountryKorea, Republic of
CityDaegu
Period27/05/200929/05/2009

Cite this

Luong, H. V., Kim, Y-M., Kim, B-K., Kim, J-M., & Kim, C-H. (2009). Parallel Approach to Fuzzy Vector Quantization for Image Compression. In 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09 (pp. 510-515). IEEE. https://doi.org/10.1109/SNPD.2009.28