• DocumentCode
    2343908
  • Title

    ICA in Image Processing: A Survey

  • Author

    Goel, Swati ; Verma, Akhilesh ; Goel, Savita ; Juneja, Komal

  • fYear
    2015
  • fDate
    13-14 Feb. 2015
  • Firstpage
    144
  • Lastpage
    149
  • Abstract
    Source separation is a problem in which signals are mixed together. It is becoming a tedious task to recuperate original components signal from the signal mixture. Blind Source Separation (BSS) is suggested as a key to the problem aiming at finding the linear representation in such a way that the components are statistically (stochastically) independent. Independent Component Analysis (ICA) is an approach that attained a wider attention and a growing significance in a diverse range of research fields for accomplishing Blind Source Separation. This paper includes preface of ICA, its variants and their list of applications in brief.
  • Keywords
    blind source separation; image processing; independent component analysis; BSS; ICA; blind source separation; image processing; independent component analysis; linear representation; research fields; Algorithm design and analysis; Classification algorithms; Feature extraction; Filter banks; Image segmentation; Independent component analysis; Kernel; Filter bank; Global features; ICA; Image model; Texture segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on
  • Conference_Location
    Ghaziabad
  • Print_ISBN
    978-1-4799-6022-4
  • Type

    conf

  • DOI
    10.1109/CICT.2015.91
  • Filename
    7078684