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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F05%3A03109390%21RIV07-GA0-21230___
rdf:type
n3:Vysledek skos:Concept
dcterms:description
This paper deals with the objective image quality evaluation. The novel method for the quality assessment of compressed images is described in this paper. Image quality scores of distorted images are estimated using oriented multichannel pyramidal decomposition and artificial neural network as a postprocessor. Performance of the implemented model for the image quality assessment has been evaluated using the database of distorted images and subjective image quality assessment. The proposed model achieves good prediction performance for used test samples. Tento poíspivek se zabývá hodnocením kvality obrazu. Je zde popsána neobvyklá metoda pro hodnocení komprimovaných obrazu. Kvalita zkreslených obrazu je odhadována s pou3itím orientované pyramidální dekompozice a umilé neuronové pro následné zpracování dat. Výkonnost implementovaného modelu pro hodnocení kvality byla vyzkou1ena na databázi zkreslených obrazu a výsledku subjektivního hodnocení kvality. Navr3ený model dosahuje na poedlo3ených testovacích vzorcích dobrých výsledku. This paper deals with the objective image quality evaluation. The novel method for the quality assessment of compressed images is described in this paper. Image quality scores of distorted images are estimated using oriented multichannel pyramidal decomposition and artificial neural network as a postprocessor. Performance of the implemented model for the image quality assessment has been evaluated using the database of distorted images and subjective image quality assessment. The proposed model achieves good prediction performance for used test samples.
dcterms:title
Image Quality Assessment Tool with the Artificial Neural Network Nástroj pro hodnocení kvality obrazu s umilou neuronovou sítí Image Quality Assessment Tool with the Artificial Neural Network
skos:prefLabel
Image Quality Assessment Tool with the Artificial Neural Network Image Quality Assessment Tool with the Artificial Neural Network Nástroj pro hodnocení kvality obrazu s umilou neuronovou sítí
skos:notation
RIV/68407700:21230/05:03109390!RIV07-GA0-21230___
n5:strany
109 ; 112
n5:aktivita
n21:P
n5:aktivity
P(GA102/05/2054), P(GD102/03/H109)
n5:dodaniDat
n10:2007
n5:domaciTvurceVysledku
n6:8983763
n5:druhVysledku
n11:D
n5:duvernostUdaju
n16:S
n5:entitaPredkladatele
n20:predkladatel
n5:idSjednocenehoVysledku
524230
n5:idVysledku
RIV/68407700:21230/05:03109390
n5:jazykVysledku
n9:eng
n5:klicovaSlova
artificial neural network; image compression; image quality
n5:klicoveSlovo
n8:artificial%20neural%20network n8:image%20compression n8:image%20quality
n5:kontrolniKodProRIV
[F2B5F2CC23FE]
n5:mistoKonaniAkce
Pilsen
n5:mistoVydani
Plzeo
n5:nazevZdroje
Applied Electronics 2005 - International Conference Pilsen
n5:obor
n14:JA
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
1
n5:projekt
n19:GA102%2F05%2F2054 n19:GD102%2F03%2FH109
n5:rokUplatneniVysledku
n10:2005
n5:tvurceVysledku
Fliegel, Karel
n5:typAkce
n13:EUR
n5:zahajeniAkce
2005-09-07+02:00
s:numberOfPages
4
n17:hasPublisher
Západočeská univerzita v Plzni
n18:isbn
80-7043-369-8
n15:organizacniJednotka
21230