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Proceedings Paper

Probability density function estimation for video in the DCT domain
Author(s): O. Dumitru; M. Mitrea; F. Prêteux; A. Pathak
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Paper Abstract

Regardless the final targeted application (compression, watermarking, texture analysis, indexation, ...), image/video modelling in the DCT domain is generally approached by tests of concordance with some well known pdfs (like Gaussian, generalised Gaussian, Laplace, Rayleigh ...). Instead of forcing the images/videos to stick to such theoretical models, our study aims at estimating the true pdf characterising their behaviour. In this respect, we considered three intensively used ways of applying DCT, namely on whole frames, on 4x4 blocks, and on 8x8 blocks. In each case, we first prove that a law modelling the corresponding coefficients exists. Then, we estimate this law by Gaussian mixtures and finally we identify the generality of such model with respect to the data on which it was computed and to the estimation method it relies on.

Paper Details

Date Published: 3 March 2008
PDF: 9 pages
Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120L (3 March 2008); doi: 10.1117/12.767469
Show Author Affiliations
O. Dumitru, Institut TELECOM / TELECOM & Management SudParis (France)
M. Mitrea, Institut TELECOM / TELECOM & Management SudParis (France)
F. Prêteux, Institut TELECOM / TELECOM & Management SudParis (France)
A. Pathak, Institut TELECOM / TELECOM & Management SudParis (France)


Published in SPIE Proceedings Vol. 6812:
Image Processing: Algorithms and Systems VI
Jaakko T. Astola; Karen O. Egiazarian; Edward R. Dougherty, Editor(s)

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