Bases for low complexity matching pursuits image coding

D. M. Monro; Yuan Yuan

doi:10.1109/ICIP.2005.1530038

Bases for low complexity matching pursuits image coding

D. M. Monro, Yuan Yuan

University of Bath, Department of Electronic & Electrical Engineering

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

4 Scopus citations

Abstract

The basis size and number of bases in a basis dictionary (codebook) are the dominant parameters in the complexity of coding data by Matching Pursuits (MP). By Basis Picking for a range of constrained basis widths on a training image coded by 1D MP, dictionaries are obtained for both still and residual images and applied in both 1D and 2D coding. On still (intra) images fidelity measured by PSNR is optimum for widths in the range 9 to 13 and dictionary sizes from 14 to 18. For residual images similar results are obtained but the bias towards narrower, smaller dictionaries is even more marked. The resulting combinations of 1D and 2D dictionaries offer significantly lower computational cost while maintaining high quality.

Original language	English
Title of host publication	IEEE International Conference on Image Processing 2005, ICIP 2005
Pages	249-252
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2005.1530038
State	Published - 2005
Externally published	Yes
Event	IEEE International Conference on Image Processing 2005, ICIP 2005 - Genova, Italy Duration: 11 Sep 2005 → 14 Sep 2005

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2
ISSN (Print)	1522-4880

Conference

Conference	IEEE International Conference on Image Processing 2005, ICIP 2005
Country/Territory	Italy
City	Genova
Period	11/09/05 → 14/09/05

Access to Document

10.1109/ICIP.2005.1530038

Cite this

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title = "Bases for low complexity matching pursuits image coding",

abstract = "The basis size and number of bases in a basis dictionary (codebook) are the dominant parameters in the complexity of coding data by Matching Pursuits (MP). By Basis Picking for a range of constrained basis widths on a training image coded by 1D MP, dictionaries are obtained for both still and residual images and applied in both 1D and 2D coding. On still (intra) images fidelity measured by PSNR is optimum for widths in the range 9 to 13 and dictionary sizes from 14 to 18. For residual images similar results are obtained but the bias towards narrower, smaller dictionaries is even more marked. The resulting combinations of 1D and 2D dictionaries offer significantly lower computational cost while maintaining high quality.",

author = "Monro, {D. M.} and Yuan Yuan",

year = "2005",

doi = "10.1109/ICIP.2005.1530038",

language = "英语",

isbn = "0780391349",

series = "Proceedings - International Conference on Image Processing, ICIP",

pages = "249--252",

booktitle = "IEEE International Conference on Image Processing 2005, ICIP 2005",

note = "IEEE International Conference on Image Processing 2005, ICIP 2005 ; Conference date: 11-09-2005 Through 14-09-2005",

}

Monro, DM & Yuan, Y 2005, Bases for low complexity matching pursuits image coding. in IEEE International Conference on Image Processing 2005, ICIP 2005., 1530038, Proceedings - International Conference on Image Processing, ICIP, vol. 2, pp. 249-252, IEEE International Conference on Image Processing 2005, ICIP 2005, Genova, Italy, 11/09/05. https://doi.org/10.1109/ICIP.2005.1530038

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AU - Yuan, Yuan

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N2 - The basis size and number of bases in a basis dictionary (codebook) are the dominant parameters in the complexity of coding data by Matching Pursuits (MP). By Basis Picking for a range of constrained basis widths on a training image coded by 1D MP, dictionaries are obtained for both still and residual images and applied in both 1D and 2D coding. On still (intra) images fidelity measured by PSNR is optimum for widths in the range 9 to 13 and dictionary sizes from 14 to 18. For residual images similar results are obtained but the bias towards narrower, smaller dictionaries is even more marked. The resulting combinations of 1D and 2D dictionaries offer significantly lower computational cost while maintaining high quality.

AB - The basis size and number of bases in a basis dictionary (codebook) are the dominant parameters in the complexity of coding data by Matching Pursuits (MP). By Basis Picking for a range of constrained basis widths on a training image coded by 1D MP, dictionaries are obtained for both still and residual images and applied in both 1D and 2D coding. On still (intra) images fidelity measured by PSNR is optimum for widths in the range 9 to 13 and dictionary sizes from 14 to 18. For residual images similar results are obtained but the bias towards narrower, smaller dictionaries is even more marked. The resulting combinations of 1D and 2D dictionaries offer significantly lower computational cost while maintaining high quality.

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T2 - IEEE International Conference on Image Processing 2005, ICIP 2005

Y2 - 11 September 2005 through 14 September 2005

ER -

Bases for low complexity matching pursuits image coding

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