title: A practical local tomography reconstruction algorithm based on a known sub-region.
abstract: A new method to reconstruct data acquired in a local tomography setup is proposed. This method uses an initial reconstruction and refines it by correcting the low-frequency artifacts, known as the cupping effect. A basis of Gaussian functions is used to correct the initial reconstruction. The coefficients of this basis are found by optimizing iteratively a fidelity term under the constraint of a known sub-region. Using a coarse basis reduces the degrees of freedom of the problem while actually correcting the cupping effect. Simulations show that the known region constraint yields an unbiased reconstruction, in accordance with uniqueness theorems stated in local tomography.
authors.affiliation: ESRF, 71 avenue des Martyrs, 38000 Grenoble, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Paleo
authors.affiliation: GIPSA-Lab, Grenoble Images Parole Signal Automatique, Institut Polytechnique de Grenoble, France.
authors.forename: Michel
authors.initials: M
authors.lastname: Desvignes
authors.affiliation: ESRF, 71 avenue des Martyrs, 38000 Grenoble, France.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Mirone
keywords: algorithm; interior problem; reconstruction; tomography