Progressive image compression algorithm based on lattice vector quantization

Anna Tatsaki; Thanos Stouraitis; Costas E. Goutis

Progressive image compression algorithm based on lattice vector quantization

Anna Tatsaki, Thanos Stouraitis, Costas E. Goutis

Electrical Engineering

University of Patras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, a low computational complexity and high efficiency algorithm for progressive image compression is presented. The image is partitioned into blocks of pixels and a prime- factor 2-D discrete cosine transform (DCT) is applied. Because of the regular structure the DCT algorithm, the coefficients could be computed in groups. Each group of DCT coefficients is then vector quantized by using the pyramid vector quantizer algorithm. Since, the DCT coefficients of each group are allocated with a different number of bits, three PVQs are used with different radii.

Original language	British English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	Naohisa Ohta, Heinz U. Lemke, J.C. Lehureau
Pages	228-236
Number of pages	9
State	Published - 1995
Event	Advanced Image and Video Communications and Storage Technologies - Amsterdam, Neth Duration: 20 Mar 1995 → 23 Mar 1995

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	2451
ISSN (Print)	0277-786X

Conference

Conference	Advanced Image and Video Communications and Storage Technologies
City	Amsterdam, Neth
Period	20/03/95 → 23/03/95

Cite this

@inproceedings{059ba789e7744ce9a2faa7f77c35ac01,

title = "Progressive image compression algorithm based on lattice vector quantization",

abstract = "In this paper, a low computational complexity and high efficiency algorithm for progressive image compression is presented. The image is partitioned into blocks of pixels and a prime- factor 2-D discrete cosine transform (DCT) is applied. Because of the regular structure the DCT algorithm, the coefficients could be computed in groups. Each group of DCT coefficients is then vector quantized by using the pyramid vector quantizer algorithm. Since, the DCT coefficients of each group are allocated with a different number of bits, three PVQs are used with different radii.",

author = "Anna Tatsaki and Thanos Stouraitis and Goutis, {Costas E.}",

year = "1995",

language = "British English",

isbn = "0819418021",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

pages = "228--236",

editor = "Naohisa Ohta and Lemke, {Heinz U.} and J.C. Lehureau",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

note = "Advanced Image and Video Communications and Storage Technologies ; Conference date: 20-03-1995 Through 23-03-1995",

}

Tatsaki, A, Stouraitis, T & Goutis, CE 1995, Progressive image compression algorithm based on lattice vector quantization. in N Ohta, HU Lemke & JC Lehureau (eds), Proceedings of SPIE - The International Society for Optical Engineering. Proceedings of SPIE - The International Society for Optical Engineering, vol. 2451, pp. 228-236, Advanced Image and Video Communications and Storage Technologies, Amsterdam, Neth, 20/03/95.

Progressive image compression algorithm based on lattice vector quantization. / Tatsaki, Anna; Stouraitis, Thanos; Goutis, Costas E.
Proceedings of SPIE - The International Society for Optical Engineering. ed. / Naohisa Ohta; Heinz U. Lemke; J.C. Lehureau. 1995. p. 228-236 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2451).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Progressive image compression algorithm based on lattice vector quantization

AU - Tatsaki, Anna

AU - Stouraitis, Thanos

AU - Goutis, Costas E.

PY - 1995

Y1 - 1995

N2 - In this paper, a low computational complexity and high efficiency algorithm for progressive image compression is presented. The image is partitioned into blocks of pixels and a prime- factor 2-D discrete cosine transform (DCT) is applied. Because of the regular structure the DCT algorithm, the coefficients could be computed in groups. Each group of DCT coefficients is then vector quantized by using the pyramid vector quantizer algorithm. Since, the DCT coefficients of each group are allocated with a different number of bits, three PVQs are used with different radii.

AB - In this paper, a low computational complexity and high efficiency algorithm for progressive image compression is presented. The image is partitioned into blocks of pixels and a prime- factor 2-D discrete cosine transform (DCT) is applied. Because of the regular structure the DCT algorithm, the coefficients could be computed in groups. Each group of DCT coefficients is then vector quantized by using the pyramid vector quantizer algorithm. Since, the DCT coefficients of each group are allocated with a different number of bits, three PVQs are used with different radii.

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M3 - Conference contribution

AN - SCOPUS:0029236579

SN - 0819418021

SN - 9780819418029

T3 - Proceedings of SPIE - The International Society for Optical Engineering

SP - 228

EP - 236

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Ohta, Naohisa

A2 - Lemke, Heinz U.

A2 - Lehureau, J.C.

T2 - Advanced Image and Video Communications and Storage Technologies

Y2 - 20 March 1995 through 23 March 1995

ER -

Progressive image compression algorithm based on lattice vector quantization

Abstract

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