About: Geometrical Constraints in Bayesian Wavelet Filtering of Images

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This paper describes a new method for the suppression of noise in images based on wavelet transform [3]. The method relies on two criteria. The first is a traditional criterion of smoothness of the image based on an approximation of the local Hőlder exponent via the wavelet coefficients. The second, novel criterion takes into account geometrical constraints, which are generally valid for natural and also simulated images. The smoothness measure and the geometrical constraints are combined in the described method in Bayesian probabilistic formulation, and are implemented as a Markov random field (MRF) image model. The manipulation of the wavelet coefficients is consequently based on the obtained probabilities. This method is proposed to quantitatively improve noise suppression comparing to classical methods based on wavelet transform. Qualitative improvement of images is also required (subjective sensation of sharpness and contrast). This paper describes a new method for the suppression of noise in images based on wavelet transform [3]. The method relies on two criteria. The first is a traditional criterion of smoothness of the image based on an approximation of the local Hőlder exponent via the wavelet coefficients. The second, novel criterion takes into account geometrical constraints, which are generally valid for natural and also simulated images. The smoothness measure and the geometrical constraints are combined in the described method in Bayesian probabilistic formulation, and are implemented as a Markov random field (MRF) image model. The manipulation of the wavelet coefficients is consequently based on the obtained probabilities. This method is proposed to quantitatively improve noise suppression comparing to classical methods based on wavelet transform. Qualitative improvement of images is also required (subjective sensation of sharpness and contrast). (en)
Title	Geometrical Constraints in Bayesian Wavelet Filtering of Images Geometrical Constraints in Bayesian Wavelet Filtering of Images (en)
skos:prefLabel	Geometrical Constraints in Bayesian Wavelet Filtering of Images Geometrical Constraints in Bayesian Wavelet Filtering of Images (en)
skos:notation	RIV/00216305:26220/04:PU46947!RIV11-MSM-26220___
http://linked.open...avai/riv/aktivita	V Z
http://linked.open...avai/riv/aktivity	V, Z(MSM 262200011), Z(MSM 262200022)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Provazník, Ivo Červinka, Tomáš
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	565508
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/04:PU46947
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	image processing, noise suppression, Markov Random Fields, applied probability, Hőlder regularity, random number (en)
http://linked.open.../riv/klicoveSlovo	random number image processing Markov Random Fields noise suppression Hőlder regularity applied probability
http://linked.open...ontrolniKodProRIV	[A13FF757D94F]
http://linked.open...v/mistoKonaniAkce	Brno
http://linked.open...i/riv/mistoVydani	Brno
http://linked.open...i/riv/nazevZdroje	Proceeedings of the 10th Conference STUDENT EEICT 2004
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...UplatneniVysledku	2004
http://linked.open...iv/tvurceVysledku	Provazník, Ivo Červinka, Tomáš
http://linked.open...vavai/riv/typAkce	CST - Celostátní
http://linked.open.../riv/zahajeniAkce	2004-04-29 (xsd:date)
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20262200011 http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20262200022
number of pages	5 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Neuveden
https://schema.org/isbn	80-214-2635-7
http://localhost/t...ganizacniJednotka	26220

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