Title :
Spherical Wiener filter
Author :
Arora, Raman ; Parthasarathy, Harish
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI
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;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4711813