Paper Info
Title
Applying binary partitioning to weighted finite automata for image compression
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 bintree partitioning-is tested on the WFA encoding method. Experimental results show that binary partitioning consistently gives higher compression ratios than the conventional quadtree 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 multilayered error protection over an often unreliable networking environment such as the UDP.
Year
DOI
Venue
2004
10.1109/ICIP.2004.1419485
ICIP
Keywords
DocType
Volume
binary partitioning,finite automata,image coding,real-time communication,trees (mathematics),image partitioning technique,fractal-based image compression techniques,fractals,data compression,grayscale images,bintree partitioning,wfa,weighted finite automata,decoding,image compression,compression ratio,transport protocol
Conference
2
ISSN
ISBN
Citations 
1522-4880
0-7803-8554-3
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Yang Kai100.34
Ghim-Hwee Ong2143.89