Inference algorithms for WFA and image compression
Fractal image compression
Matrix computations (3rd ed.)
Group Theoretical Methods in Image Understanding
Group Theoretical Methods in Image Understanding
Refining image compression with weighted finite automata
DCC '96 Proceedings of the Conference on Data Compression
Compression of Silhouette-like Images Based on WFA
DCC '97 Proceedings of the Conference on Data Compression
Weighted finite automata for video compression
IEEE Journal on Selected Areas in Communications
Weighted Finite Automata encoding over Thai language
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
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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.