• DocumentCode
    1862810
  • Title

    Spherical Wiener filter

  • Author

    Arora, Raman ; Parthasarathy, Harish

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    549
  • Lastpage
    552
  • Abstract
    A novel group-theoretic method is presented for denoising a three-dimensional scene in isotropic noise. Images of the scene at varying depths are regarded as reference stochastic processes on the unit sphere to formulate Weiner-Hopf equations for estimating the image at any given depth. These comprise a set of coupled linear integral equations on the unit sphere and are solved using Peter-Weyl theory of Fourier transform on the rotation group. The computational complexity of this algorithm is reduced using bi-invariance of the image correlations with respect to the stabilizer subgroup of the rotation group.
  • Keywords
    Fourier transforms; Wiener filters; computational complexity; group theory; image denoising; integral equations; 3D scene denoising; Fourier transform; Peter-Weyl theory; Weiner-Hopf equations; computational complexity; group-theoretic method; image correlations bi-invariance; isotropic noise; linear integral equations; rotation group; spherical Wiener filter; stabilizer subgroup; Application software; Computational complexity; Image reconstruction; Integral equations; Layout; Noise reduction; Signal processing; Smoothing methods; Surface reconstruction; Wiener filter; 3D surface data; Wiener filtering; smoothing methods; spherical harmonics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1765-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2008.4711813
  • Filename
    4711813