About: A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In this paper, we present a novel approach to predict the perceived image quality. Properties of the Human Visual System (HVS) were exploited to select a set of suitable metrics. These metrics are extracted while comparing the reference and distorted image. Mutual Information (MI) and Principal Component Analysis (PCA) were used to obtain an optimal set of objective features that best describe the perceived image quality in respect to subjective scores from human observers. The impairment feature vector is for¬warded to the Artificial Neural Network (ANN) where the features are combined and the predicted quality score is computed. Parameters of the ANN are adjusted using Mean Opinion Scores (MOS) obtained from the group of assessors. It is shown that the proposed image quality assessment model can achieve high correlation with the subjective image quality ratings. Possible incorporation of the model into a perceptual image-coding algorithm is proposed. In this paper, we present a novel approach to predict the perceived image quality. Properties of the Human Visual System (HVS) were exploited to select a set of suitable metrics. These metrics are extracted while comparing the reference and distorted image. Mutual Information (MI) and Principal Component Analysis (PCA) were used to obtain an optimal set of objective features that best describe the perceived image quality in respect to subjective scores from human observers. The impairment feature vector is for¬warded to the Artificial Neural Network (ANN) where the features are combined and the predicted quality score is computed. Parameters of the ANN are adjusted using Mean Opinion Scores (MOS) obtained from the group of assessors. It is shown that the proposed image quality assessment model can achieve high correlation with the subjective image quality ratings. Possible incorporation of the model into a perceptual image-coding algorithm is proposed. (en) V tomto elánkuje popsán nový poístup predikce obrazové kvality. Vhodné metriky byly vybrány s ohledem na vlastnosti lidského visuálního systému (HVS). Tyto metriky jsou vypoeítány porovnáním originálního a zkresleného obrazu. Na poedzpracování dat byla pou3ita pokroeilá metoda (Mutual Information – MI, Principal Component Analysis – PCA) tak, aby odhad kvality z modelu byl blízký subjektivním soudum pozorovatelu. Vektor zkreslujících parametru je zpracován ANN, kde jsou tyto parametry zkombinovány a ureena predikce kvality. Parametry ANN byly nastaveny s pou3itím subjektivních soudu skupinou pozorovatelu (MOS). Dobrá predikení schopnost modelu byla demonstrována ve smyslu vysoké korelace mezi subjektivními soudy MOS a výstupem neuronové síti. V záviru elánku je návrh implementace modelu do perceptuálního kompresního algoritmu. (cs)
Title	A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms Model vyu3ívající umilou neuronovou síť pro perceptuální hodnocení obrazové kvality v kompresních algoritmech pro kompresi obrazu (cs) A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms (en)
skos:prefLabel	A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms Model vyu3ívající umilou neuronovou síť pro perceptuální hodnocení obrazové kvality v kompresních algoritmech pro kompresi obrazu (cs) A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms (en)
skos:notation	RIV/68407700:21230/06:03120527!RIV07-GA0-21230___
http://linked.open.../vavai/riv/strany	631507-1 ; 631507-10
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(GA102/05/2054), Z(MSM6840770014)
http://linked.open...vai/riv/dodaniDat	2007
http://linked.open...aciTvurceVysledku	Fliegel, Karel
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	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	463592
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/06:03120527
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	artificial neural network; image compression; image processing; image quality (en)
http://linked.open.../riv/klicoveSlovo	artificial neural network image processing image quality image compression
http://linked.open...ontrolniKodProRIV	[04E8585DCBDA]
http://linked.open...v/mistoKonaniAkce	San Diego
http://linked.open...i/riv/mistoVydani	Bellingham
http://linked.open...i/riv/nazevZdroje	Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Qualitative aspects of audiovisual information processing in multimedia systems
http://linked.open...UplatneniVysledku	2006
http://linked.open...iv/tvurceVysledku	Fliegel, Karel
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2006-08-13 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Výzkum perspektivních informačních a komunikačních technologií
number of pages	10 (xsd:int)
http://purl.org/ne...btex#hasPublisher	SPIE
https://schema.org/isbn	0-8194-6394-9
http://localhost/t...ganizacniJednotka	21230
is http://linked.open...avai/riv/vysledek of	A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms

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