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Description
  • 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. (cs)
  • 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.
  • 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. (en)
Title
  • Image Quality Assessment Tool with the Artificial Neural Network
  • Image Quality Assessment Tool with the Artificial Neural Network (en)
  • Nástroj pro hodnocení kvality obrazu s umilou neuronovou sítí (cs)
skos:prefLabel
  • Image Quality Assessment Tool with the Artificial Neural Network
  • Image Quality Assessment Tool with the Artificial Neural Network (en)
  • Nástroj pro hodnocení kvality obrazu s umilou neuronovou sítí (cs)
skos:notation
  • RIV/68407700:21230/05:03109390!RIV07-GA0-21230___
http://linked.open.../vavai/riv/strany
  • 109 ; 112
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/05/2054), P(GD102/03/H109)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 524230
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/05:03109390
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • artificial neural network; image compression; image quality (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F2B5F2CC23FE]
http://linked.open...v/mistoKonaniAkce
  • Pilsen
http://linked.open...i/riv/mistoVydani
  • Plzeo
http://linked.open...i/riv/nazevZdroje
  • Applied Electronics 2005 - International Conference Pilsen
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Fliegel, Karel
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Západočeská univerzita v Plzni
https://schema.org/isbn
  • 80-7043-369-8
http://localhost/t...ganizacniJednotka
  • 21230
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