Transform-based fine-coarse vector quantization

Kin Man Lam; Wan Chi Siu; Kai Ming Tse

Transform-based fine-coarse vector quantization

Kin Man Lam
, Wan Chi Siu
, Kai Ming Tse

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

Fine-coarse vector quantization (FCVQ) is a fast method for searching an unstructured vector quantization codebook. This approach imposes slight distortion to the image and requires substantially large storage. The storage requirement restricts the dimension of the vector blocks hence the performance of this quantization scheme. In this paper, the FCVQ is designed in the transform domain (FCVQ-TB) to provide a possible solution to the problem on memory requirement. Experiments are given to evaluate the performance of the FCVQ-TB.

Original language	English
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	Publ by IEEE
Pages	671-674
Number of pages	4
Volume	1
ISBN (Print)	0780312813
Publication status	Published - 1 Jan 1993
Event	1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, United States Duration: 3 May 1993 → 6 May 1993

Conference

Conference	1993 IEEE International Symposium on Circuits and Systems
Country/Territory	United States
City	Chicago, IL
Period	3/05/93 → 6/05/93

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Cite this

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title = "Transform-based fine-coarse vector quantization",

abstract = "Fine-coarse vector quantization (FCVQ) is a fast method for searching an unstructured vector quantization codebook. This approach imposes slight distortion to the image and requires substantially large storage. The storage requirement restricts the dimension of the vector blocks hence the performance of this quantization scheme. In this paper, the FCVQ is designed in the transform domain (FCVQ-TB) to provide a possible solution to the problem on memory requirement. Experiments are given to evaluate the performance of the FCVQ-TB.",

author = "Lam, \{Kin Man\} and Siu, \{Wan Chi\} and Tse, \{Kai Ming\}",

year = "1993",

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AU - Siu, Wan Chi

AU - Tse, Kai Ming

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Y1 - 1993/1/1

N2 - Fine-coarse vector quantization (FCVQ) is a fast method for searching an unstructured vector quantization codebook. This approach imposes slight distortion to the image and requires substantially large storage. The storage requirement restricts the dimension of the vector blocks hence the performance of this quantization scheme. In this paper, the FCVQ is designed in the transform domain (FCVQ-TB) to provide a possible solution to the problem on memory requirement. Experiments are given to evaluate the performance of the FCVQ-TB.

AB - Fine-coarse vector quantization (FCVQ) is a fast method for searching an unstructured vector quantization codebook. This approach imposes slight distortion to the image and requires substantially large storage. The storage requirement restricts the dimension of the vector blocks hence the performance of this quantization scheme. In this paper, the FCVQ is designed in the transform domain (FCVQ-TB) to provide a possible solution to the problem on memory requirement. Experiments are given to evaluate the performance of the FCVQ-TB.

UR - https://www.scopus.com/pages/publications/0027168113

M3 - Conference article published in proceeding or book

SN - 0780312813

VL - 1

SP - 671

EP - 674

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - Publ by IEEE

T2 - 1993 IEEE International Symposium on Circuits and Systems

Y2 - 3 May 1993 through 6 May 1993

ER -

Transform-based fine-coarse vector quantization

Abstract

Conference

ASJC Scopus subject areas

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Cite this