Reconstruction in tomography from severe incomplete projection data using multiresolution analysis and optimization

摘要

This paper proposed a new optimization approach over whole distribution region in tomography for smooth distributions from severe incomplete projection data. The multiresolution analysis proposed by Mallet (1989) based on wavelet transform with orthonormal bases proposed by Daubechies (1988) is applied to reduce the number of parameters for optimization and to ignore the details of wavelet representations at high resolution level. Results of reconstructing from 3 or 6 projections for two test distributions demonstrates the usefulness of this approach of tomography for severe incomplete projection data.