Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41842
Title: Applying binary partitioning to weighted finite automata for image compression
Authors: Kai, Y.
Hwee, O.G. 
Issue Date: 2004
Source: Kai, Y.,Hwee, O.G. (2004). Applying binary partitioning to weighted finite automata for image compression. Proceedings - International Conference on Image Processing, ICIP 5 : 1061-1064. ScholarBank@NUS Repository.
Abstract: Fractal-based image compression techniques give efficient decoding time with primitive hardware requirements, which favors real-time communication purposes. One such technique, the Weighted Finite Automata (WFA) is studied on grayscale images. An improved image partitioning technique - the binary or bin-tree partitioning - is tested on the WFA encoding method. Experimental results show that binary partitioning consistently gives higher compression ratios than the conventional quad-tree partitioning method. Moreover, the ability to decode images progressively rendering finer and finer details can be used to display the image over a congested and loss-prone network such as the Image Transport Protocol (ITP) for the Internet, as well as to pave way for multi-layered error protection over an often unreliable networking environment such as the UDP. ©2004 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/41842
ISSN: 15224880
Appears in Collections:Staff Publications

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