Radon transform inversion via Wiener filtering over the Euclidean motion group

Inthispaper we formulatethe Radon transform asa wnvolution integral over the Euclidean motion group (SE(2)) and provideaminimummeansquare error(MMSE) stochastic deconvolution method for the Radon transform inversion. Proposed approach provides a fundamentally new formulation that can modelnonstationarysignalandnoise fields. Key components of our development are the Fourier transform over SE(2),stochastic processes indexed by groups and fast implementation of the SE(2)Fourier transform. Numerical studies presentedheredemonstrate that the method yields image quality that is comparable or better than the filtered backprojection algorithm. Apart from X-ray tomographic image reconstruction, the proposed deconvolution method is directly applicable to inverse radiotherapy, and broad range of science and engineering problems in computer vision, pattern recognition, robotics as well as protein science.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Can Evren Yarman, Birsen Yazici
• Keywords: Fourier Transform, ICIP 2003, Image Processing, Radon Transform Asa, Radon Transform Inversion, SE(2)Fourier Transform, Stochastic Deconvolution Method