• DocumentCode
    2340082
  • Title

    Blur identification using an adaptive ADALINE network

  • Author

    He, Wei-Guo ; Li, Shao-fa ; Hu, Gui-wu

  • Author_Institution
    Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • Volume
    9
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    5314
  • Abstract
    There are different techniques available for solving of the restoration problem including Fourier domain techniques, regularization methods, and so on. But without knowing at least approximate parameters of the blur, these filters show poor results. Fourier domain techniques seriously suffer from the additive noise and non-uniform motion. In this paper a new approach is proposed for blur parameters identification using an adaptive ADALINE network. The weights of the ADALINE network are taken as the estimation of the blur PSF. Simulation results for the non-uniform straight motion-blurred images demonstrate the identification and restoration is effective.
  • Keywords
    Fourier transforms; image motion analysis; image restoration; neural nets; random noise; Fourier domain; adaptive ADALINE network; additive noise; blur estimation; blur parameter identification; image restoration; motion-blurred images; neural network; nonuniform motion; point spread function; regularization method; Adaptive filters; Adaptive systems; Additive noise; Computer science; Convolution; Degradation; Frequency domain analysis; Helium; Image restoration; Motion estimation; Neural network; image restoration; motion-blurred images; point spread function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527882
  • Filename
    1527882