• DocumentCode
    3247593
  • Title

    A correlation method of image quality assessment based on SVM and GA

  • Author

    Wang, Lei ; Ding, Wenrui ; Xiang, Jinwu ; Cui, Le

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    6
  • Lastpage
    10
  • Abstract
    In this paper, we propose a correlation method to assess image quality based on support vector machine (SVM) and genetic algorithm (GA). Instead of the simple linear function to correlate objective indicators with subjective scores of images, we introduce SVM for the correlation function, make GA as the search algorithm, and finally get the image quality assessment model. The results of experiments show: It is effective to introduce SVM to make correlation between objective indicators and subjective scores for image quality assessment; the correlation between objective indicators and subjective scores is better by using SVM based on GA.
  • Keywords
    correlation methods; genetic algorithms; image processing; support vector machines; correlation method; genetic algorithm; image quality assessment model; support vector machine; Artificial neural networks; Correlation; Gallium; Image quality; Kernel; Support vector machines; Training; correlation method; genetic algorithm; image quality assessment; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2010 3rd International Congress on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6513-2
  • Type

    conf

  • DOI
    10.1109/CISP.2010.5646285
  • Filename
    5646285