Similarity enrichment in image compression through weighted finite automata

Zhuhan Jiang; Bruce Litow; Olivier de Vel

doi:10.1007/3-540-44968-x_44

Similarity enrichment in image compression through weighted finite automata

Zhuhan Jiang, Bruce Litow, Olivier de Vel

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

18 Citations (Scopus)

Abstract

We propose and study in details a similarity enrichment scheme for the application to the image compression through the exten-sion of the weighted nite automata (WFA). We then develop a mech-anism with which rich families of legitimate similarity images can be systematically created so as to reduce the overall WFA size, leading to an eventual better WFA-based compression performance. A number of desirable properties, including WFA of minimum states, have been estab-lished for a class of packed WFA. Moreover, a codec based on a special extended WFA is implemented to exemplify explicitly the performance gain due to extended WFA under otherwise the same conditions.

Original language	English
Title of host publication	Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings
Editors	Ding-Zhu Du, Peter Eades, Vladimir Estivill-Castro, Xuemin Lin, Arun Sharma
Publisher	Springer Verlag
Pages	447-456
Number of pages	10
ISBN (Print)	3540677879, 9783540677871
DOIs	https://doi.org/10.1007/3-540-44968-x_44
Publication status	Published - 2000
Externally published	Yes
Event	6th Annual International Conference on Computing and Combinatorics, COCOON 2000 - Sydney, Australia Duration: 26 Jul 2000 → 28 Jul 2000

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1858
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th Annual International Conference on Computing and Combinatorics, COCOON 2000
Country/Territory	Australia
City	Sydney
Period	26/07/00 → 28/07/00

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2000.

Access to Document

10.1007/3-540-44968-x_44

Cite this

Jiang, Z., Litow, B., & de Vel, O. (2000). Similarity enrichment in image compression through weighted finite automata. In D.-Z. Du, P. Eades, V. Estivill-Castro, X. Lin, & A. Sharma (Eds.), Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings (pp. 447-456). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1858). Springer Verlag. https://doi.org/10.1007/3-540-44968-x_44

Jiang, Zhuhan ; Litow, Bruce ; de Vel, Olivier. / Similarity enrichment in image compression through weighted finite automata. Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings. editor / Ding-Zhu Du ; Peter Eades ; Vladimir Estivill-Castro ; Xuemin Lin ; Arun Sharma. Springer Verlag, 2000. pp. 447-456 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We propose and study in details a similarity enrichment scheme for the application to the image compression through the exten-sion of the weighted nite automata (WFA). We then develop a mech-anism with which rich families of legitimate similarity images can be systematically created so as to reduce the overall WFA size, leading to an eventual better WFA-based compression performance. A number of desirable properties, including WFA of minimum states, have been estab-lished for a class of packed WFA. Moreover, a codec based on a special extended WFA is implemented to exemplify explicitly the performance gain due to extended WFA under otherwise the same conditions.",

author = "Zhuhan Jiang and Bruce Litow and {de Vel}, Olivier",

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Jiang, Z, Litow, B & de Vel, O 2000, Similarity enrichment in image compression through weighted finite automata. in D-Z Du, P Eades, V Estivill-Castro, X Lin & A Sharma (eds), Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1858, Springer Verlag, pp. 447-456, 6th Annual International Conference on Computing and Combinatorics, COCOON 2000, Sydney, Australia, 26/07/00. https://doi.org/10.1007/3-540-44968-x_44

Similarity enrichment in image compression through weighted finite automata. / Jiang, Zhuhan; Litow, Bruce; de Vel, Olivier.
Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings. ed. / Ding-Zhu Du; Peter Eades; Vladimir Estivill-Castro; Xuemin Lin; Arun Sharma. Springer Verlag, 2000. p. 447-456 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1858).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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AB - We propose and study in details a similarity enrichment scheme for the application to the image compression through the exten-sion of the weighted nite automata (WFA). We then develop a mech-anism with which rich families of legitimate similarity images can be systematically created so as to reduce the overall WFA size, leading to an eventual better WFA-based compression performance. A number of desirable properties, including WFA of minimum states, have been estab-lished for a class of packed WFA. Moreover, a codec based on a special extended WFA is implemented to exemplify explicitly the performance gain due to extended WFA under otherwise the same conditions.

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Jiang Z, Litow B, de Vel O. Similarity enrichment in image compression through weighted finite automata. In Du DZ, Eades P, Estivill-Castro V, Lin X, Sharma A, editors, Computing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings. Springer Verlag. 2000. p. 447-456. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-44968-x_44

Similarity enrichment in image compression through weighted finite automata

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