Multi-energy penalized maximum-likelihood reconstruction for x-ray security imaging

David G. Politte; Jingwei Lu; Joseph A. O'Sullivan; Eric Johnson; Carl Bosch

doi:10.1117/12.2263343

1 May 2017 Multi-energy penalized maximum-likelihood reconstruction for x-ray security imaging

David G. Politte; Jingwei Lu; Joseph A. O'Sullivan; Eric Johnson; Carl Bosch

Author Affiliations +

Proceedings Volume 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II; 101870D (2017) https://doi.org/10.1117/12.2263343
Event: SPIE Defense + Security, 2017, Anaheim, California, United States

Abstract

X-ray imaging for security screening is a challenging application that requires simultaneous satisfaction of seemingly incompatible constraints, including low cost, high throughput, and reliable detection of threats. We take a principled computational imaging approach to system design. Mathematical models of the underlying physics and a Huber-class penalty function yield a penalized maximum-likelihood problem. We extend our iterative algorithm for computing linear attenuation coefficients to use multiple energy bins in the SureScan x1000, which has an unconventional, fixed-source geometry. The goal is to maintain the spatial resolution of the single-energy reconstruction while providing information for material characterization used for detection of threats.

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David G. Politte, David G. Politte, Jingwei Lu, Jingwei Lu, Joseph A. O'Sullivan, Joseph A. O'Sullivan, Eric Johnson, Eric Johnson, Carl Bosch, Carl Bosch, } "Multi-energy penalized maximum-likelihood reconstruction for x-ray security imaging", Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 101870D (1 May 2017); doi: 10.1117/12.2263343; https://doi.org/10.1117/12.2263343

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