Expectation maximisation algorithms for terahertz transmission tomography | Zendy

Benoît Recur | Zendy; Hugo Balacey | Zendy; Patrick Mounaix | Zendy

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Expectation maximisation algorithms for terahertz transmission tomography

Author(s) -

Benoît Recur,

Hugo Balacey,

Patrick Mounaix

Publication year - 2014

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.2062476

Subject(s) - terahertz radiation , tomography , computer science , tomographic reconstruction , opacity , iterative reconstruction , transmission (telecommunications) , energy (signal processing) , scanner , optics , sample (material) , reconstruction algorithm , algorithm , computer vision , artificial intelligence , physics , telecommunications , quantum mechanics , thermodynamics

International audienceTerahertz (THz) tomography is a recently developed imaging technique allowing 3D inspection of opaque objects. In this paper, we develop an ordered subsets convex algorithm for THz transmission tomography (THz-OSC). Since the reconstruction quality is highly depending on the THz beam energy, we investigate afterwards a multienergy version of the algorithm in order to provide a more accurate reconstruction of the acquired sample. This multi-energy approach is validated by reconstructing data from tomographic acquisitions measured with a 84/287 GHz transmission scanner. Then we discuss how this dual-energy approach could be able to extract physical properties of acquired samples in addition to improving 3D reconstruction

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