An index coding algorithm for image vector quantization

Pei Yin Chen; Ren Der Chen

doi:10.1109/TCE.2003.1261261

An index coding algorithm for image vector quantization

Pei Yin Chen^*
, Ren Der Chen

^*Corresponding author for this work

Southern Taiwan University of Science and Technology

Research output: Contribution to journal › Journal Article › peer-review

13 Scopus citations

Abstract

This paper presents a lossless index-coding algorithm for image vector quantization. Using the concept of dynamic tree coding, the method can encode the output index map of a memoryless vector quantizer efficiently without introducing any extra coding distortion. Experiment results show that it achieves better compression efficiency than other lossless index coding schemes. The computation complexity of the method is quite low and its memory requirement is small. Hence, it can be easily implemented by hardware and applied to many real-time applications.

Original language	English
Pages (from-to)	1513-1520
Number of pages	8
Journal	IEEE Transactions on Consumer Electronics
Volume	49
Issue number	4
DOIs	https://doi.org/10.1109/TCE.2003.1261261
State	Published - 11 2003
Externally published	Yes

Keywords

Image compression
Lossless index coding
Vector quantization

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abstract = "This paper presents a lossless index-coding algorithm for image vector quantization. Using the concept of dynamic tree coding, the method can encode the output index map of a memoryless vector quantizer efficiently without introducing any extra coding distortion. Experiment results show that it achieves better compression efficiency than other lossless index coding schemes. The computation complexity of the method is quite low and its memory requirement is small. Hence, it can be easily implemented by hardware and applied to many real-time applications.",

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AB - This paper presents a lossless index-coding algorithm for image vector quantization. Using the concept of dynamic tree coding, the method can encode the output index map of a memoryless vector quantizer efficiently without introducing any extra coding distortion. Experiment results show that it achieves better compression efficiency than other lossless index coding schemes. The computation complexity of the method is quite low and its memory requirement is small. Hence, it can be easily implemented by hardware and applied to many real-time applications.

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KW - Lossless index coding

KW - Vector quantization

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An index coding algorithm for image vector quantization

Abstract

Keywords

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