A distributed implementation of fuzzy clustering and switching of linear regression models for lossless compression of imagery and 3D data

Author

Aiazzi, B. ; Alba, P. ; Alparone, L. ; Baronti, S. ; Lotti, F. ; Mattei, A.

Author_Institution

Ist. di Ricerca sulle Onde Elettromagnetiche, CNR, Firenze, Italy

fYear

1998

fDate

7-9 Dec 1998

Firstpage

382

Lastpage

387

Abstract

A distributed implementation of a new method for reversible compression of both 2D and 3D data is presented. A classified prediction is first trained through fuzzy clustering; then, data decorrelation is accomplished by prediction in a fuzzy fashion. Context-based adaptive arithmetic coding is tailored to the prediction errors to enhance entropy coding. Results and comparisons with other schemes are presented and discussed together with computational issues

Keywords

adaptive codes; arithmetic codes; data compression; differential pulse code modulation; distributed processing; entropy codes; fuzzy systems; image classification; image coding; pattern clustering; prediction theory; statistical analysis; 2D data; 3D data; classified prediction; computational issues; context-based adaptive arithmetic coding; data decorrelation; distributed implementation; entropy coding; fuzzy DPCM algorithm; fuzzy clustering; imagery; linear regression models; lossless compression; prediction errors; reversible compression; Arithmetic; Clustering algorithms; Data communication; Decorrelation; Entropy coding; Image coding; Linear regression; Prototypes; Radiometry; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Signal Processing, 1998 IEEE Second Workshop on

Conference_Location

Redondo Beach, CA

Print_ISBN

0-7803-4919-9

Type

conf

DOI

10.1109/MMSP.1998.738966

Filename

738966