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Proceedings Paper

A utilization of GMM for scientific images modeling
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Paper Abstract

This paper deals with modeling of scientific and multimedia images in the wavelet domain. Images transformed into wavelet domain have a special shape of probability density function (PDF). Thus wavelet coefficients PDFs are usually modeled using generalized Laplacian PDF model (GLM), which is characterized by two parameters. The wavelet coefficients modeling can be more efficient, while the Gaussian mixture model (GMM) is utilized. GMM model is given by addition of at least two Gaussian PDFs with different standard deviations. There will be presented equation system derived by moment method for GMM models parameters estimation. The equation system was derived for an addition of two GMM models. So it is suitable for advanced denoising systems, where an addition of two GMM random variables is considered (e.g. dark current in astronomical images).

Paper Details

Date Published: 2 September 2009
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 74431R (2 September 2009); doi: 10.1117/12.826008
Show Author Affiliations
Jan Švihlík, Institute of Chemical Technology Prague (Czech Republic)
Karel Fliegel, Czech Technical Univ. in Prague (Czech Republic)

Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)

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