Results in Applied Mathematics (May 2020)
Automatic regularization for tomographic image reconstruction
Abstract
The phase retrieval process of imaging a sample can be modeled as a simple convolution process. Sometimes, such a convolution depends on physical parameters of the sample which are difficult to estimate a priori. In this case, a blind choice for those parameters usually lead to wrong results, e.g., extracting information from the reconstructed images. In this manuscript, we propose a simple connection between phase-retrieval algorithms and optimization strategies, which lead us to ways of numerically determining the physical parameters. Keywords: Regularization, Phase, Tomography, Synchrotron