| Accelerating the optimization of requantization codebook for vector quantization. | |
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MedLine Citation:
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PMID: 17491459 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Requantization is an important technique for variable-rate data compression and communication and optimal design for requantization is key to guaranteeing the minimization of the requantization noise. Recently, an iterative optimization algorithm for designing the requantization codebook was proposed. We develop further results regarding the acceleration of the algorithm and a better understanding of the problem of requantization. In particular, our result shows that the quantization and requantization processes can be decoupled into two nearly independent sequential stages, and that requantization does not need the original training vectors. All these features pave the way toward real-time variable-rate data compression and transmission over heterogeneous networks. Simulation results support the theory and the advantages of our method. |
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Authors:
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Yun Zhou; Yi Wan |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Volume: 16 ISSN: 1057-7149 ISO Abbreviation: IEEE Trans Image Process Publication Date: 2007 May |
Date Detail:
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Created Date: 2007-05-11 Completed Date: 2007-06-07 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9886191 Medline TA: IEEE Trans Image Process Country: United States |
Other Details:
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Languages: eng Pagination: 1281-8 Citation Subset: IM |
Affiliation:
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Signals and Information Processing, Lanzhou Uriversity, Lanzhou 730000, China. zhouyui02@st.lzu.edu.cn |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Computer Simulation Data Compression / methods* Data Interpretation, Statistical Image Enhancement / methods* Image Interpretation, Computer-Assisted / methods* Models, Statistical Numerical Analysis, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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