DocumentCode :
3011976
Title :
A lossless image compression technique using generic peano pattern mask tree
Author :
Hossain, Mohammad Kabir ; Imam, S.M. ; Hasan, Khondker Shajadul ; Perrizo, William
Author_Institution :
Dept. Comput. Sci. & Eng., North South Univ., Dhaka
fYear :
2008
fDate :
24-27 Dec. 2008
Firstpage :
317
Lastpage :
322
Abstract :
Digital image processing has become ubiquitous in our daily life and the demands to produce and process images are ever increasing. Large amounts of space are required to store these images. Image compression techniques are in high demand as they allow reduction in this storage space. The basis for image compression, as is for most other compression techniques, is to remove redundant and unimportant data. Lossless image compression techniques retain the original information in compact form and do not introduce any errors when decompressed. In this paper, we discuss such a lossless technique using a data structure that we name ldquogeneric Peano pattern mask treerdquo. It is an improvement over a previously discussed Lossless Image compression technique - ldquoPeano pattern mask treerdquo. Both these structures are based on the data structure - Peano mask tree.
Keywords :
Bayes methods; data compression; data mining; decision trees; image classification; image coding; probability; tree data structures; Bayesian probability; P-tree based decision tree classification; data-mining; digital image processing; generic peano pattern mask tree; image storage space; lossless image compression technique; peano mask tree data structure; Computer science; Data mining; Data structures; Digital images; Image coding; Image reconstruction; Image storage; Information technology; Neodymium; Tree data structures; Data mining Ready; Generic Peano Pattern Mask Tree; Lossless Image Compression; Peano Mask Tree; Peano Pattern Mask Tree; Peano Tree;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Technology, 2008. ICCIT 2008. 11th International Conference on
Conference_Location :
Khulna
Print_ISBN :
978-1-4244-2135-0
Electronic_ISBN :
978-1-4244-2136-7
Type :
conf
DOI :
10.1109/ICCITECHN.2008.4802980
Filename :
4802980
Link To Document :
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