Distributed Lossy Source Coding Using Real-Number Codes
We show how real-number codes can be used to compress correlated sources, and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible...
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| Vydáno v: | 2012 IEEE Vehicular Technology Conference (VTC Fall) s. 1 - 5 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.09.2012
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| Témata: | |
| ISBN: | 1467318809, 9781467318808 |
| ISSN: | 1090-3038 |
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| Abstract | We show how real-number codes can be used to compress correlated sources, and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible to model correlation between continuous-valued sources more realistically and correct quantization error when the sources are completely correlated. The encoding and decoding procedures are described in detail, for discrete Fourier transform (DFT) codes. Reconstructed signal, in the mean-squared error sense, is seen to be better than or close to quantization error level in the conventional approach. |
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| AbstractList | We show how real-number codes can be used to compress correlated sources, and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible to model correlation between continuous-valued sources more realistically and correct quantization error when the sources are completely correlated. The encoding and decoding procedures are described in detail, for discrete Fourier transform (DFT) codes. Reconstructed signal, in the mean-squared error sense, is seen to be better than or close to quantization error level in the conventional approach. |
| Author | Vaezi, M. Labeau, F. |
| Author_xml | – sequence: 1 givenname: M. surname: Vaezi fullname: Vaezi, M. email: mojtaba.vaezi@mail.mcgill.ca organization: Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada – sequence: 2 givenname: F. surname: Labeau fullname: Labeau, F. email: fabrice.labeau@mcgill.ca organization: Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada |
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| Snippet | We show how real-number codes can be used to compress correlated sources, and establish a new framework for distributed lossy source coding, in which we... |
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| SubjectTerms | Correlation Decoding Discrete Fourier transforms Quantization Source coding Vectors |
| Title | Distributed Lossy Source Coding Using Real-Number Codes |
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