doi: 10.4304/jsw.6.2.322-330
A Content-based Classified Hierarchical Vector Quantization Algorithm for Volume Compression
- 1 School of Mathematics and Information Engineering, Jiaxing University, Jiaxing, Zhejiang, China
- 2 School of Computer and Communication Engineering, Hunan University, Changsha, Hunan, China
- 3 Department of Computer Science and Technology, Huaihua University, Huaihua, China
- 4 Jiangsu Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Soochow, China
Abstract
An improved volumetric compression algorithm is presented in this paper. Histogram technique is used for analyzing the trait of volume data. The volume data is then partitioned into volume bricks which will be classified into two groups, the blocks with meaningless information as one group(also called empty blocks), and those with meaningful information as the other group(also called object blocks). An efficient hierarchical VQ is applied to compress object blocks while for empty blocks, nothing is saved. Compare with analogous Volume Compression algorithm, experimental results demonstrate the proposed algorithm not only can improve the compression rate significantly on the premise of the good quality of reconstruction image, but also can obtain fast decoding speed.
Keywords
- Vector quantization
- volume Classify
- Ob
How to Cite
Li-Ping Zhao, Guang-Xue Yue, De-Gui Xiao, Xu Zhou, Xiang Yu, and Fei Yu, "A Content-based Classified Hierarchical Vector Quantization Algorithm for Volume Compression," Journal of Software, vol. 6, no. 2, pp. 322-330, 2011. https://doi.org/ 10.4304/jsw.6.2.322-330
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).