• DocumentCode
    248757
  • Title

    Fast L1 Gaussian convolution via domain splitting

  • Author

    Yoshizawa, Shingo ; Yokota, Hideo

  • Author_Institution
    Image Process. Res. Team, RIKEN, Wako, Japan
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2908
  • Lastpage
    2912
  • Abstract
    This paper proposes a fast and accurate approximation algorithm to convolve a L1 Gaussian function with images. Our new algorithm is based on splitting a pixel domain into representative regions where we can efficiently perform discrete convolutions. Our algorithm is applicable to non-uniform pixels with linear computational complexity. We examine it numerically in terms of speed, precision, and quality. We also introduce a novel edge-aware filter by using our algorithm.
  • Keywords
    Gaussian processes; approximation theory; filtering theory; image representation; image resolution; approximation algorithm; discrete convolutions; domain splitting; fast L1 Gaussian convolution; linear computational complexity; novel edge-aware filter; pixel domain; representative regions; Approximation algorithms; Approximation methods; Convolution; Equations; Image edge detection; Kernel; Transforms; Domain Transform; Edge-aware Filtering; Fast Discrete Convolution; Laplace Distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025588
  • Filename
    7025588