DocumentCode
1437413
Title
Compression ratio boundaries for predictive signal compression
Author
Pianykh, Oleg S. ; Tyler, John M.
Author_Institution
Dept. of Radiol., Louisiana State Univ. Med. Center, New Orleans, LA, USA
Volume
10
Issue
2
fYear
2001
fDate
2/1/2001 12:00:00 AM
Firstpage
323
Lastpage
326
Abstract
Predictive regressional models like DPCM are widely used in digital signal compression. This paper analyzes the relationship that exists between the predictive model fitness and the resultant reduction of the first-order signal entropy, and finds the lossless compression ratio C as a function of predictive model correlation ρ
Keywords
correlation methods; data compression; differential pulse code modulation; entropy; image coding; prediction theory; DPCM; compression ratio boundaries; digital signal compression; first-order signal entropy reduction; image compression; lossless compression ratio; predictive model correlation; predictive model fitness; predictive regressional models; predictive signal compression; Decorrelation; Digital images; Discrete cosine transforms; Entropy; Image coding; Pixel; Predictive models; Signal analysis; Transform coding; Wavelet transforms;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.902297
Filename
902297
Link To Document