A multi-layered image coding using multiple transforms

Li Xiong Liu; Yuan Quan Wang; Wei Wei Wang

doi:10.1109/ICMLC.2008.4621000

A multi-layered image coding using multiple transforms

Li Xiong Liu^*, Yuan Quan Wang, Wei Wei Wang

^*Corresponding author for this work

School of Computer Science and Technology

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

Abstract

This paper proposes a new multi-layered image coding algorithm based on wavelet and matching pursuit transforms. The original image is divided into smooth and edge layer and texture layer, Different compression algorithms of coding are adopted to each different layer in order to achieve optimization for the entire image. Case studies have demonstrated that this coding method can capture texture and edge characteristics efficiently. Besides, the quality of reconstructed image is better than traditional single wavelet image coding algorithm at low bit rates.

Original language	English
Title of host publication	Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Pages	3445-3450
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLC.2008.4621000
Publication status	Published - 2008
Event	7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China Duration: 12 Jul 2008 → 15 Jul 2008

Publication series

Name	Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Volume	6

Conference

Conference	7th International Conference on Machine Learning and Cybernetics, ICMLC
Country/Territory	China
City	Kunming
Period	12/07/08 → 15/07/08

Keywords

Image coding
Matching pursuit
Multi-layer image
Texture coding
Wavelet

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10.1109/ICMLC.2008.4621000

Cite this

Liu, L. X., Wang, Y. Q., & Wang, W. W. (2008). A multi-layered image coding using multiple transforms. In Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC (pp. 3445-3450). Article 4621000 (Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC; Vol. 6). https://doi.org/10.1109/ICMLC.2008.4621000

@inproceedings{d082e336822a44f987650ecf61307501,

title = "A multi-layered image coding using multiple transforms",

abstract = "This paper proposes a new multi-layered image coding algorithm based on wavelet and matching pursuit transforms. The original image is divided into smooth and edge layer and texture layer, Different compression algorithms of coding are adopted to each different layer in order to achieve optimization for the entire image. Case studies have demonstrated that this coding method can capture texture and edge characteristics efficiently. Besides, the quality of reconstructed image is better than traditional single wavelet image coding algorithm at low bit rates.",

keywords = "Image coding, Matching pursuit, Multi-layer image, Texture coding, Wavelet",

author = "Liu, {Li Xiong} and Wang, {Yuan Quan} and Wang, {Wei Wei}",

year = "2008",

doi = "10.1109/ICMLC.2008.4621000",

language = "English",

isbn = "9781424420964",

series = "Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC",

pages = "3445--3450",

booktitle = "Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC",

note = "7th International Conference on Machine Learning and Cybernetics, ICMLC ; Conference date: 12-07-2008 Through 15-07-2008",

}

Liu, LX, Wang, YQ & Wang, WW 2008, A multi-layered image coding using multiple transforms. in Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC., 4621000, Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC, vol. 6, pp. 3445-3450, 7th International Conference on Machine Learning and Cybernetics, ICMLC, Kunming, China, 12/07/08. https://doi.org/10.1109/ICMLC.2008.4621000

A multi-layered image coding using multiple transforms. / Liu, Li Xiong; Wang, Yuan Quan; Wang, Wei Wei.
Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC. 2008. p. 3445-3450 4621000 (Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC; Vol. 6).

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

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AU - Wang, Yuan Quan

AU - Wang, Wei Wei

PY - 2008

Y1 - 2008

N2 - This paper proposes a new multi-layered image coding algorithm based on wavelet and matching pursuit transforms. The original image is divided into smooth and edge layer and texture layer, Different compression algorithms of coding are adopted to each different layer in order to achieve optimization for the entire image. Case studies have demonstrated that this coding method can capture texture and edge characteristics efficiently. Besides, the quality of reconstructed image is better than traditional single wavelet image coding algorithm at low bit rates.

AB - This paper proposes a new multi-layered image coding algorithm based on wavelet and matching pursuit transforms. The original image is divided into smooth and edge layer and texture layer, Different compression algorithms of coding are adopted to each different layer in order to achieve optimization for the entire image. Case studies have demonstrated that this coding method can capture texture and edge characteristics efficiently. Besides, the quality of reconstructed image is better than traditional single wavelet image coding algorithm at low bit rates.

KW - Image coding

KW - Matching pursuit

KW - Multi-layer image

KW - Texture coding

KW - Wavelet

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DO - 10.1109/ICMLC.2008.4621000

M3 - Conference contribution

AN - SCOPUS:57849121209

SN - 9781424420964

T3 - Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC

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BT - Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC

T2 - 7th International Conference on Machine Learning and Cybernetics, ICMLC

Y2 - 12 July 2008 through 15 July 2008

ER -

A multi-layered image coding using multiple transforms

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Keywords

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