A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
In order to improve the quality of X-ray Computed Tomography (CT) reconstruction for Non Destructive Testing (NDT), we propose a hierarchical prior modeling with a Bayesian approach. In this paper we present a new hierarchical structure for the inverse problem of CT by using a multivariate Studentt prior which enforces sparsity and preserves edges. This model can be adapted to the piecewise continuous image reconstruction problems. We demonstrate the feasibility of this method by comparing withdoi:10.1109/icassp.2016.7471802 dblp:conf/icassp/WangMGD16 fatcat:z3ch5v3f4nc5zmgszxgaeruham