• DocumentCode
    2154094
  • Title

    Combine EMD and ICA to Learn Image Bases

  • Author

    Dai, Fang ; Xue, Jianru ; Zheng, Nanning

  • Volume
    3
  • fYear
    2008
  • fDate
    27-30 May 2008
  • Firstpage
    494
  • Lastpage
    497
  • Abstract
    A method of learning image bases from natural images is proposed in this paper. Natural image is decomposed into structure mode and non-structure mode by using Empirical Mode Decomposition (EMD) technique. The structure mode is made up of the first two Intrinsic Mode Functions (IMF) that represent the structure information of image. The other IMFs and residual image compose the non-structure mode. A structure bases dictionary or a non-structure bases dictionary is obtained by using Independent Component Analysis (ICA) on structure mode or non-structure mode respectively. The image can be expressed by using the obtained dictionaries according to different attribution of image regions to implement image coding and sparse representation. Compared with ICA, the structure bases can better capture structure information of natural images, and the separation of the structure bases and non- structure bases can be profitable for the different description of different images information.
  • Keywords
    Artificial intelligence; Dictionaries; Frequency; Gabor filters; Humans; Image coding; Independent component analysis; Intelligent robots; Principal component analysis; Signal processing; Empirical Mode Decomposition; Image bases; Intrinsic Mode Function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2008. CISP '08. Congress on
  • Conference_Location
    Sanya, China
  • Print_ISBN
    978-0-7695-3119-9
  • Type

    conf

  • DOI
    10.1109/CISP.2008.606
  • Filename
    4566533