DocumentCode :
1826839
Title :
Image data compression using multiple bases representation
Author :
Tilki, John F. ; Beex, A. A Louis
Author_Institution :
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
fYear :
1994
fDate :
20-22 Mar 1994
Firstpage :
457
Lastpage :
461
Abstract :
Digitized images contain huge amounts of information which strain, or exceed, the capacity for their real-time processing, storage, and retrieval. Various compression techniques have been developed to reduce the amount of data necessary for representation. The authors report on a hybrid image data compression procedure based on a multiple bases representation. The multiple bases representation technique described utilizes advantages of transform coding, vector quantization, and predictive coding, while aiming to circumvent the associated disadvantages of each. Preliminary results indicate that this procedure can outperform conventional compression methods, and yield high compression ratios while avoiding prohibitive computational complexity
Keywords :
encoding; image coding; linear predictive coding; vector quantisation; hybrid image data compression; image data compression; multiple bases representation; predictive coding; transform coding; vector quantization; Capacitive sensors; Computational complexity; Data compression; Image coding; Image retrieval; Image storage; Information retrieval; Predictive coding; Transform coding; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Theory, 1994., Proceedings of the 26th Southeastern Symposium on
Conference_Location :
Athens, OH
ISSN :
0094-2898
Print_ISBN :
0-8186-5320-5
Type :
conf
DOI :
10.1109/SSST.1994.287833
Filename :
287833
Link To Document :
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