Multi-resolution Source Coding Using Entropy Constrained Dithered Scalar Quantization

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http://doi.ieeecomputersociety.org/10.1109/DCC.2004.1281447

Data Compression Conference (DCC '04)

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	Qian Zhao, Hanying Feng, Michelle Effros, "Multi-resolution Source Coding Using Entropy Constrained Dithered Scalar Quantization," Data Compression Conference, pp. 22, Data Compression Conference (DCC '04), 2004.

	BibTex	x
	@article{ 10.1109/DCC.2004.1281447, author = {Qian Zhao and Hanying Feng and Michelle Effros}, title = {Multi-resolution Source Coding Using Entropy Constrained Dithered Scalar Quantization}, journal ={Data Compression Conference}, volume = {0}, year = {2004}, issn = {1068-0314}, pages = {22}, doi = {http://doi.ieeecomputersociety.org/10.1109/DCC.2004.1281447}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Compression Conference TI - Multi-resolution Source Coding Using Entropy Constrained Dithered Scalar Quantization SN - 1068-0314 SP EP A1 - Qian Zhao, A1 - Hanying Feng, A1 - Michelle Effros, PY - 2004 KW - null VL - 0 JA - Data Compression Conference ER -

Qian Zhao, Oracle Corp., Redwood City, CA

Hanying Feng, Stanford University, CA

Michelle Effros, California Institute of Technology, Pasadena, CA

In this paper, we build multi-resolution source codes using entropy constrained dithered scalar quantizers. We demonstrate that for n-dimensional random vectors, dithering followed by uniform scalar quantization and then by entropy coding achieves performance close to the n-dimensional optimum for a multi-resolution source code. Based on this result, we propose a practical code design algorithm and compare its performance with that of the Set Partitioning in Hierarchical Trees (SPIHT) algorithm on natural images.

Citation:

Qian Zhao, Hanying Feng, Michelle Effros, "Multi-resolution Source Coding Using Entropy Constrained Dithered Scalar Quantization," dcc, pp.22, Data Compression Conference (DCC '04), 2004

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