A tomographic reconstruction method with generalized natural basis functions and a priori information
Series-expansion tomography methods that use natural basis functions (NBFs), also show natural pixels, often use iterative solution techniques or solution by truncated singular valve decomposition (TSVD). Here solution by constrained optimization is proposed. It is shown that significant improvements in the tomographic reconstructions can be obtained, in particular when the coverage by the imaging system is irregular. The analogy between regular NFBs and the filtered backprojection or convolution-backprojection tomography method suggests maximum smoothness in projection space as object function (i.e. a priori information) in the constrained optimization. A further improvement was found by employing NFBs that correspond to a bilinear interpolation in projection space. The new NBF method is compared with various tomography methods: constrained optimization with local basis functions, NBFs and TSVD, and an iterative projection-space reconstruction method.
Bibliographic Reference: Report: JET-P(99)46
Availability: Available from JET Joint Undertaking, Abingdon, Oxfordshire (GB)
Record Number: 200012768 / Last updated on: 2000-09-20
Original language: en
Available languages: en