Please use this identifier to cite or link to this item:
|Title:||A binary partitioning approach to image compression using weighted finite automata for large images||Authors:||Ong, G.H.
Weighted finite automata
|Issue Date:||2006||Citation:||Ong, G.H., Yang, K. (2006). A binary partitioning approach to image compression using weighted finite automata for large images. Computers and Mathematics with Applications 51 (11) : 1705-1714. ScholarBank@NUS Repository.||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. © 2006 Elsevier Ltd. All rights reserved.||Source Title:||Computers and Mathematics with Applications||URI:||http://scholarbank.nus.edu.sg/handle/10635/25333||ISSN:||08981221|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 18, 2018
WEB OF SCIENCETM
checked on Dec 24, 2018
checked on Apr 18, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.