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