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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 644266260
doi: 10.4316/AECE


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  2/2013 - 6

Asymmetrical Two-Level Scalar Quantizer with Extended Huffman Coding for Compression of Laplacian Source

PERIC, Z. See more information about PERIC, Z. on SCOPUS See more information about PERIC, Z. on IEEExplore See more information about PERIC, Z. on Web of Science, NIKOLIC, J. See more information about  NIKOLIC, J. on SCOPUS See more information about  NIKOLIC, J. on SCOPUS See more information about NIKOLIC, J. on Web of Science, VELIMIROVIC, L. See more information about  VELIMIROVIC, L. on SCOPUS See more information about  VELIMIROVIC, L. on SCOPUS See more information about VELIMIROVIC, L. on Web of Science, STANKOVIC, M. See more information about  STANKOVIC, M. on SCOPUS See more information about  STANKOVIC, M. on SCOPUS See more information about STANKOVIC, M. on Web of Science, ALEKSIC, D. See more information about ALEKSIC, D. on SCOPUS See more information about ALEKSIC, D. on SCOPUS See more information about ALEKSIC, D. on Web of Science
 
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Download PDF pdficon (656 KB) | Citation | Downloads: 287 | Views: 2,067

Author keywords
distortion, entropy coding, Huffman coding, quantization, signal to noise ratio

References keywords
peric(5), huffman(5), introduction(4), coding(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-05-31
Volume 13, Issue 2, Year 2013, On page(s): 39 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.02006
Web of Science Accession Number: 000322179400006
SCOPUS ID: 84878941715

Abstract
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This paper proposes a novel model of the two-level scalar quantizer with extended Huffman coding. It is designed for the average bit rate to approach the source entropy as close as possible provided that the signal to quantization noise ratio (SQNR) value does not decrease more than 1 dB from the optimal SQNR value. Assuming the asymmetry of representation levels for the symmetric Laplacian probability density function, the unequal probabilities of representation levels are obtained, i.e. the proper basis for further implementation of lossless compression techniques is provided. In this paper, we are concerned with extended Huffman coding technique that provides the shortest length of codewords for blocks of two or more symbols. For the proposed quantizer with extended Huffman coding the convergence of the average bit rate to the source entropy is examined in the case of two to five symbol blocks. It is shown that the higher SQNR is achieved by the proposed asymmetrical quantizer with extended Huffman coding when compared with the symmetrical quantizers with extended Huffman coding having equal average bit rates.


References | Cited By  «-- Click to see who has cited this paper

[1] N. S. Jayant, P. Noll, Digital Coding of Waveforms: Principles and Applications to Speech and Video, New Jersey, Prentice Hall, 1984.

[2] D. C. Hankerson, G. A. Harris, P. D. Johnson, Introduction to Information Theory and Data Compression, Boca Raton, Chapman & Hall/CRC, 2003.
[CrossRef]


[3] L. Hanzo, C. Somerville, J. Woodard, Voice and Audio Compression for Wireless Communications, London, John Wiley & Sons, 2007.
[CrossRef] [SCOPUS Times Cited 1]


[4] K. Sayood, Introduction to Data Compression, San Francisco, Elsevier, 2006.

[5] D. Salomon, A Concise Introduction to Data Compression, New York, Springer, 2008.
[CrossRef]


[6] A. R. Elabdalla, M. Irshid, "An Efficient Bitwise Huffman Coding Technique Based on Source Mapping", Computer and Electrical Engineering, Vol. 27, pp. 265-272, 2001.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 13]


[7] A. Zolghadr-E-Asli, S. Alipour, "An Effective Method for Still Image Compression/ Decompression for Transmission on PSTN Lines Based on Modifications of Huffman Coding", Computer and Electrical Engineering, Vol. 30, pp. 129-145, 2004.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 7]


[8] R. L. Rabiner, W. R.Schafer, "Introduction to Digital Speech Processing", Foundations and Trends in Signal Processing, Vol. 1, pp 1-194, 2007.
[CrossRef] [SCOPUS Times Cited 72]


[9] P. Fenwick, "Huffman Code Efficiencies for Extensions of Sources", IEEE Transaction on Communications, Vol 43, pp. 163-165, 1995.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]


[10] M. Dincic, Z. Peric, "Design of Quantizers with Huffman Coding for Laplacian Source", Electronics and Electrical Engineering, Vol. 10, pp. 129-132, 2010.

[11] Z. Peric, J. Nikolic, "An Effective Method for Initialization of Lloyd-Max's Algorithm of Optimal Scalar Quantization for Laplacian Source", Informatica, Vol. 18, pp. 279-288, 2007.

[12] D. Marco, D. L. Neuhoff, "Low-Resolution Scalar Quantization for Gaussian and Laplacian Sources with Absolute and Squared Error Distortion Measures", Technical report, 2006.

[13] Z. Peric, M. Dincic, M. Petkovic, "Design of a Hybrid Quantizer with Variable Length Code", Fundamenta informaticae , Vol. 98, pp. 233-256, 2010.

[14] K. Fredriksson, J. Tarhio, "Efficient String Matching in Huffman Compressed Texts", Fundamenta Informaticae, Vol. 62, pp. 1-16, 2004.

[15] V. Despotovic, Z. Peric, L. Velimirovic, V. Delic, "DPCM with forward gain-adaptive quantizer and switched first order predictor for high quality speech signals", Advances in Electrical and Computer Engineering, Vol. 10, pp. 95-98, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 4] [SCOPUS Times Cited 6]


[16] V. Despotovic, Z. Peric, "ADPCM Using a Second-order Switched Predictor and Adaptive Quantizer", Advances in Electrical and Computer Engineering, Vol. 11, pp. 61-61, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]




References Weight

Web of Science® Citations for all references: 25 TCR
SCOPUS® Citations for all references: 104 TCR

Web of Science® Average Citations per reference: 1 ACR
SCOPUS® Average Citations per reference: 6 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2016-12-05 13:08 in 51 seconds.




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