Paper Info
Title
A binary partitioning approach to image compression using weighted finite automata for large images
Abstract
Fractal-based image compression techniques give efficient decoding time with primitive hardware requirements, and favor 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 for large images. 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. Also, the proposed partitioning approach can be parallelized to reduce its high encoding complexity.
Year
DOI
Venue
2006
10.1016/j.camwa.2006.05.008
Computers & Mathematics with Applications
Keywords
Field
DocType
binary partitioning,proposed partitioning approach,image transport protocol,fractal-based image compression technique,image compression,data compression,higher compression ratio,grayscale image,binary partitioning approach,improved image,large image,high encoding complexity,weighted finite automata,wfa encoding method,quadtree partitioning,finer detail,weighted finite automaton,transport protocol,compression ratio
Data compression ratio,Set partitioning in hierarchical trees,Computer science,Algorithm,Decoding methods,Data compression,Rendering (computer graphics),Image compression,Grayscale,Quadtree
Journal
Volume
Issue
ISSN
51
11
Computers and Mathematics with Applications
Citations 
PageRank 
References 
3
0.68
4
Authors
2
Name
Order
Citations
PageRank
Ghim-Hwee Ong1143.89
Kai Yang26415.67