Deterministic discrete tomography reconstruction by energy minimization method on the triangular grid

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Elsevier

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info:eu-repo/semantics/closedAccess

Abstract

In this paper we consider the binary tomography reconstruction problem on the triangular grid. A deterministic energy-minimization method is proposed. The new method is based on the convex-concave regularization approach and uses the Spectral Projected Gradient optimization algorithm. The proposed method shows significant advantages, regarding the quality of the reconstructions and required running time, in comparison with the previously suggested reconstruction method based on the stochastic Simulated Annealing algorithm. Experimental results, using regular hexagon shaped test images, are presented and analyzed. (C) 2014 Elsevier B.V. All rights reserved.

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Discrete tomography, Triangular grid, Energy-minimization, Deterministic optimization, Convex-concave regularization, Spectral Projected Gradient

Journal or Series

Pattern Recognition Letters

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49

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