• DocumentCode
    2313602
  • Title

    Color Image Restoration Based on Split Bregman Iteration Algorithm

  • Author

    Liya, Yi ; Xiaolei, Lu ; FuRong, Wang

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2010
  • fDate
    9-11 Feb. 2010
  • Firstpage
    184
  • Lastpage
    187
  • Abstract
    In this paper, we modify the Split Bregman algorithm for color image restoration with the edge-preserving color image total variation model. The observed blurred images are assumed to be degraded by within channel and cross channel blurs. Our proposed algorithm is based on the Split Bregman process and simply requires Fast Fourier Transform in each iteration. Experimental comparisons using various types of blurs are reported, and the results show that, the proposed method significantly outperforms existing methods, such as the variable splitting alternative minimization algorithm and that adopted by MATLAB deblurring function, in terms of both objective signal to noise ratio and subjective vision quality. This demonstrates the efficiency of our proposed algorithms.
  • Keywords
    fast Fourier transforms; image colour analysis; image restoration; blurred images; color image restoration; edge-preserving color image total variation model; fast Fourier transform; split Bregman iteration algorithm; split Bregman process; Color; Degradation; Fast Fourier transforms; Gray-scale; Image restoration; Layout; Machine learning; Machine learning algorithms; Mathematical model; TV; cross channel; image restoration; split Bregman iteration; total variation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Computing (ICMLC), 2010 Second International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4244-6006-9
  • Electronic_ISBN
    978-1-4244-6007-6
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.22
  • Filename
    5460745