An inference implementation based on extended weighted finite automata

Jiang, Zhuhan, Litow, Bruce, and de Vel, Oliver (2001) An inference implementation based on extended weighted finite automata. In: Australian Computer Science Communications (23) pp. 100-108. From: 24th Australasian Computer Science Conference ACSC 2001, 29 January - 2 February 2001, Gold Coast, Queensland.

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A similarity enrichment scheme for the application to image compression through the extension of weighted finite automata (WFA) has been recently proposed [1] by the authors. We shall here first establish additional theoretical results on the extended WFA of minimum states. We then devise an effective inference algorithm and its concrete implementation through the consideration of WFA of minimum states, image approximation in least squares, state image intensity generation via Gauss-Seidel method, as well as the improvement on the decoding efficiency. The codec implemented this way will exemplify explicitly the performance gain due to extended WFA under otherwise the same conditions.

Item ID: 14593
Item Type: Conference Item (Research - E1)
ISBN: 978-0-7695-0969-3
Keywords: image compression; inference algorithm; self-similarity; weighted finite automata
Date Deposited: 11 Oct 2017 22:59
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0802 Computation Theory and Mathematics > 080299 Computation Theory and Mathematics not elsewhere classified @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
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