An improved fast encoding algorithm for vector quantization

In the current information age, people have to access various information. With the popularization of the Internet in all kinds of information fields and the development of communication technology, more and more information has to be processed in high speed. Data compression is one of the technique...

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Veröffentlicht in:Journal of the American Society for Information Science and Technology Jg. 55; H. 1; S. 81 - 87
Hauptverfasser: Liu, Li-Juan, Shen, Xu-Bang, Zou, Xue-Cheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.01.2004
Wiley
Wiley Periodicals Inc
Schlagworte:
Academic Achievement
Algorithms
Applied sciences
Artificial intelligence
Codes
Communications technology
Compression
Computer mediated communication
Computer science; control theory; systems
Computer simulation
Computerized information storage and retrieval
Data compression
Data processing
Data structures
Decomposition
Encoding
Exact sciences and technology
Image compression
Image quality
Information science
Information technology
Internet
Mathematical models
Mathematics
Memory
Pattern recognition. Digital image processing. Computational geometry
Recognition (Achievement)
Science
Search algorithms
Searching
Simulation
Storage
Studies
System on chip
Telecommunications
Vector quantization
Wavelet transforms
China
Vector quantization
Image processing
Data compression
ISSN:1532-2882, 2330-1635, 1532-2890, 2330-1643
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Beschreibung
Zusammenfassung:In the current information age, people have to access various information. With the popularization of the Internet in all kinds of information fields and the development of communication technology, more and more information has to be processed in high speed. Data compression is one of the techniques in information data processing applications and spreading images. The objective of data compression is to reduce data rate for transmission and storage. Vector quantization (VQ) is a very powerful method for data compression. One of the key problems for the basic VQ method, i.e., full search algorithm, is that it is computationally intensive and is difficult for real time processing. Many fast encoding algorithms have been developed for this reason. In this paper, we present a reasonable half‐L2‐norm pyramid data structure and a new method of searching and processing codewords to significantly speed up the searching process especially for high dimensional vectors and codebook with large size; reduce the actual requirement for memory, which is preferred in hardware implementation system, e.g., SOC (system‐on‐chip); and produce the same encoded image quality as full search algorithm. Simulation results show that the proposed method outperforms some existing related fast encoding algorithms.
Bibliographie:istex:6A3A7E5BE2906E4FF8513E1DB5A77C51125AC880
ark:/67375/WNG-9D7G6MTG-T
ArticleID:ASI10343
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1532-2882
2330-1635
1532-2890
2330-1643
DOI:10.1002/asi.10343