Haytham A. Ali1,2,*, Hiroyuki Kudo1
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3741-3756, 2022, DOI:10.32604/cmc.2022.029394
Abstract This paper proposes a new level-set-based shape recovery approach that can be applied to a wide range of binary tomography reconstructions. In this technique, we derive generic evolution equations for shape reconstruction in terms of the underlying level-set parameters. We show that using the appropriate basis function to parameterize the level-set function results in an optimization problem with a small number of parameters, which overcomes many of the problems associated with the traditional level-set approach. More concretely, in this paper, we use Gaussian functions as a basis function placed at sparse grid points to represent the parametric level-set function and… More >
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