NDLI: Vector quantization using matrix decompositions of codebooks for image coding

Content Provider	IEEE Xplore Digital Library
Author	Jar-Ferr Yang Chiou-Liang Lu Po-Wen Chin
Copyright Year	1991
Description	Author affiliation: Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan (Jar-Ferr Yang; Chiou-Liang Lu; Po-Wen Chin)
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.<>
Starting Page	308
Ending Page	311
File Size	464565
Page Count	4
File Format	PDF
ISBN	0780300505
DOI	10.1109/ISCAS.1991.176335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-06-11
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Matrix decomposition Image coding Singular value decomposition Degradation Image storage ISDN HDTV Pulse modulation Delta modulation
Content Type	Text
Resource Type	Article

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Vector quantization using matrix decompositions of codebooks for image coding