Vector quantization using matrix decompositions of codebooks for image coding

Jar Ferr Yang; Chiou Liang Lu; Po Wen Chin

Vector quantization using matrix decompositions of codebooks for image coding

Jar Ferr Yang, Chiou Liang Lu, Po Wen Chin

Institute of Computer and Communication Engineering

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

Methods of using vector quantization combined with singular value decomposition (SVD) and simplified least square estimation (LSE) compensation are proposed. The complexity of computation is decreased by determining a simpler scheme to obtain the same optimal estimated singular values as the LSE. With the assistance of the matrix-decomposed codebooks, edge degradation and compression rate can be improved by using a few least-square-compensated singular values. Avoiding the high computational complexity of SVD during the encoding and decoding procedures and achieving good quality of image coding are the main contributions of the present work.

Original language	English
Pages (from-to)	308-311
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
Publication status	Published - 1991 Dec 1
Event	1991 IEEE International Symposium on Circuits and Systems Part 1 (of 5) - Singapore, Singapore Duration: 1991 Jun 11 → 1991 Jun 14

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

Fingerprint Dive into the research topics of 'Vector quantization using matrix decompositions of codebooks for image coding'. Together they form a unique fingerprint.

Cite this

@article{e4cfe1a6e34b4234a2d303c6b7956c7c,

title = "Vector quantization using matrix decompositions of codebooks for image coding",

abstract = "Methods of using vector quantization combined with singular value decomposition (SVD) and simplified least square estimation (LSE) compensation are proposed. The complexity of computation is decreased by determining a simpler scheme to obtain the same optimal estimated singular values as the LSE. With the assistance of the matrix-decomposed codebooks, edge degradation and compression rate can be improved by using a few least-square-compensated singular values. Avoiding the high computational complexity of SVD during the encoding and decoding procedures and achieving good quality of image coding are the main contributions of the present work.",

author = "Yang, {Jar Ferr} and Lu, {Chiou Liang} and Chin, {Po Wen}",

year = "1991",

month = dec,

day = "1",

language = "English",

volume = "1",

pages = "308--311",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "1991 IEEE International Symposium on Circuits and Systems Part 1 (of 5) ; Conference date: 11-06-1991 Through 14-06-1991",

}

TY - JOUR

T1 - Vector quantization using matrix decompositions of codebooks for image coding

AU - Yang, Jar Ferr

AU - Lu, Chiou Liang

AU - Chin, Po Wen

PY - 1991/12/1

Y1 - 1991/12/1

N2 - Methods of using vector quantization combined with singular value decomposition (SVD) and simplified least square estimation (LSE) compensation are proposed. The complexity of computation is decreased by determining a simpler scheme to obtain the same optimal estimated singular values as the LSE. With the assistance of the matrix-decomposed codebooks, edge degradation and compression rate can be improved by using a few least-square-compensated singular values. Avoiding the high computational complexity of SVD during the encoding and decoding procedures and achieving good quality of image coding are the main contributions of the present work.

AB - Methods of using vector quantization combined with singular value decomposition (SVD) and simplified least square estimation (LSE) compensation are proposed. The complexity of computation is decreased by determining a simpler scheme to obtain the same optimal estimated singular values as the LSE. With the assistance of the matrix-decomposed codebooks, edge degradation and compression rate can be improved by using a few least-square-compensated singular values. Avoiding the high computational complexity of SVD during the encoding and decoding procedures and achieving good quality of image coding are the main contributions of the present work.

UR - http://www.scopus.com/inward/record.url?scp=0026404991&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026404991&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0026404991

VL - 1

SP - 308

EP - 311

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

SN - 0271-4310

T2 - 1991 IEEE International Symposium on Circuits and Systems Part 1 (of 5)

Y2 - 11 June 1991 through 14 June 1991

ER -