Title :
A Novel Generalized Particle Model for Lossless Data Compression
Author :
Shuai, Dianxun ; Shuai, Dianxun
Author_Institution :
Dept. of Comput. Sci. & Eng., East China Univ. of Sci. & Tech., Shanghai
Abstract :
This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. Local rules for particle movement in GPM, parallel algorithm and its implementation structure to generate the desired predictive coding are discussed. The proposed GPM approach has advantages in terms of encoding speed, parallelism, scalability, simplicity, and easy hardware implementation over other sequential lossless compression methods
Keywords :
data compression; parallel algorithms; generalized particle model; lossless data compression; parallel algorithm; prediction coding; Data compression; Encoding; Image coding; Image reconstruction; Multimedia databases; Parallel processing; Phased arrays; Predictive coding; Predictive models; Wavelet transforms;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2006. SNPD 2006. Seventh ACIS International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-2611-X
DOI :
10.1109/SNPD-SAWN.2006.6
