Optimal restoration of noisy 3D x-ray data via shearlet decompositions

Demetrio Labate; Glenn R. Easley; Kanghui Guo

doi:10.1117/12.2023680

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26 September 2013 Optimal restoration of noisy 3D x-ray data via shearlet decompositions

Demetrio Labate, Glenn R. Easley, Kanghui Guo

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Proceedings Volume 8858, Wavelets and Sparsity XV; 885807 (2013) https://doi.org/10.1117/12.2023680
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

In a recent work, it was shown that the shearlet representation provides a useful formula for the reconstruction of 3D objects from their X-ray projections. One major advantage of this approach is that it yields a near-optimal rate of convergence in estimating piecewise smooth objects from 3D X-ray projections which are corrupted by white Gaussian noise. In this work, we provide numerical demonstrations to illustrate the effectiveness of this method and its performance as compared with other X-ray data restoration algorithms.

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Demetrio Labate, Glenn R. Easley, and Kanghui Guo "Optimal restoration of noisy 3D x-ray data via shearlet decompositions", Proc. SPIE 8858, Wavelets and Sparsity XV, 885807 (26 September 2013); https://doi.org/10.1117/12.2023680

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