Multigrid inversion algorithms for Poisson noise model-based tomographic reconstruction

Seungseok Oh; Charles A. Bouman; Kevin J. Webb

doi:10.1117/12.598771

11 March 2005 Multigrid inversion algorithms for Poisson noise model-based tomographic reconstruction

Seungseok Oh, Charles A. Bouman, Kevin J. Webb

Proceedings Volume 5674, Computational Imaging III; (2005) https://doi.org/10.1117/12.598771
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

A multigrid inversion approach is proposed to solve Poisson noise model-based inverse problems. The algorithm works by moving up and down in resolution with a set of coarse scale cost functions, which incorporates a coarse scale Poisson mean defined in low resolution data and image spaces. Applications of the approach to Bayesian reconstruction algorithms in transmission and emission tomography are presented. Simulation results indicate that the proposed multigrid approach results in significant improvement in convergence speed compared to the fixed-grid iterative coordinate descent (ICD) method.

Citation Download Citation

Seungseok Oh, Charles A. Bouman, and Kevin J. Webb "Multigrid inversion algorithms for Poisson noise model-based tomographic reconstruction", Proc. SPIE 5674, Computational Imaging III, (11 March 2005); https://doi.org/10.1117/12.598771

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