Reduced and coded sensing methods for x-ray based security

Current x-ray technologies provide security personnel with non-invasive sub-surface imaging and contraband detection in various portal screening applications such as checked and carry-on baggage as well as cargo. Computed tomography (CT) scanners generate detailed 3D imagery in checked bags; however, these scanners often require significant power, cost, and space. These tomography machines are impractical for many applications where space and power are often limited such as checkpoint areas. Reducing the amount of data acquired would help reduce the physical demands of these systems. Unfortunately this leads to the formation of artifacts in various applications, thus presenting significant challenges in reconstruction and classification. As a result, the goal is to maintain a certain level of image quality but reduce the amount of data gathered. For the security domain this would allow for faster and cheaper screening in existing systems or allow for previously infeasible screening options due to other operational constraints. While our focus is predominantly on security applications, many of the techniques can be extended to other fields such as the medical domain where a reduction of dose can allow for safer and more frequent examinations. This dissertation aims to advance data reduction algorithms for security motivated x-ray imaging in three main areas: (i) development of a sensing aware dimensionality reduction framework, (ii) creation of linear motion tomographic method of object scanning and associated reconstruction algorithms for carry-on baggage screening, and (iii) the application of coded aperture techniques to improve and extend imaging performance of nuclear resonance fluorescence in cargo screening. The sensing aware dimensionality reduction framework extends existing dimensionality reduction methods to include knowledge of an underlying sensing mechanism of a latent variable. This method provides an improved classification rate over classical methods on both a synthetic case and a popular face classification dataset. The linear tomographic method is based on non-rotational scanning of baggage moved by a conveyor belt, and can thus be simpler, smaller, and more reliable than existing rotational tomography systems at the expense of more challenging image formation problems that require special model-based methods. The reconstructions for this approach are comparable to existing tomographic systems. Finally our coded aperture extension of existing nuclear resonance fluorescence cargo scanning provides improved observation signal-to-noise ratios. We analyze, discuss, and demonstrate the strengths and challenges of using coded aperture techniques in this application and provide guidance on regimes where these methods can yield gains over conventional methods

An Engineering Trade Space Analysis for a Space-Based Hyperspectral Chromotomographic Scanner

Hyperspectroscopy for fast transient events such as battlefield explosions is an undeveloped area of spectral imaging. This thesis is a discussion of issues involved with taking a laboratory design for a rotating prism hyperspectral chromotomographic (CT) instrument and producing a first approximation satellite payload design, operating scheme and trade space analysis to support demonstration of this technology in low-earth orbit. This instrument promises the capability of adding a time dimension to the normal spatial and spectral data produced by most hyperspectral imagers. The ultimate goal is to conduct experiments demonstrating the ultimate viability of spectral definition of transient combustion events on the ground from space. The experiment will be designed to use the CT scanner to collect, store and transmit data from any suitable target on the earth surface in the orbit footprint

Development and Characterization of a Chromotomosynthetic Hyperspectral Imaging System

A chromotomosynthetic imaging (CTI) methodology based upon mathematical reconstruction of a set of 2-D spectral projections to collect high-speed (100 Hz) 3-D hyperspectral data cube has been proposed. The CTI system can simultaneously provide usable 3-D spatial and spectral information, provide high-frame rate slitless 1-D spectra, and generate 2-D imagery equivalent to that collected with no prism in the optical system. The wavelength region where prism dispersion is highest (500 nm) is most sensitive to loss of spectral resolution in the presence of systematic error, while wavelengths 600 nm suffer mostly from a shift of the spectral peaks. The quality of the spectral resolution in the reconstructed hyperspectral imagery was degraded by as much as a factor of two in the blue spectral region with less than 1° total angular error in mount alignment in the two axes of freedom. Even with no systematic error, spatial artifacts from the reconstruction limit the ability to provide adequate spectral imagery without specialized image reconstruction techniques as targets become more spatially and spectrally uniform

Development and Demonstration of a Field-Deployable fast Chromotomographic Imager

A field deployable hyperspectral imager utilizing chromotomography (CT), with a direct vision prism (DVP) as the dispersive element, has been constructed at AFIT. This research is focused on the development and demonstration of the CT imager. An overview of hyperspectral imaging, chromotomography, a synopsis of reconstruction algorithms, and other CT instruments are given. The importance of component alignment, instrument calibration, and exact prism angular position data are discussed. A simplistic \shift and add reconstruction algorithm was utilized for this research. Although limited in its ability to reconstruct a spatially and spectrally diverse scene, the algorithm was adequate for the testing and characterization of the CT imager. The AFIT instrument is currently the fastest known DVP based hyperspectral CT imager and is a prototype for a planned space-based system. The instrument has the ability to capture spatial and spectral data of static and transient scenes. Spectral and spatial reconstructions of static scenes are presented in the Experimental Results and Analysis section of this paper. These reconstruction illustrate the effectiveness of the instrument to collect spatial and spectral data. More importantly, the imager can capture spectral data of rapidly evolving scenes such as explosions. The spectrum of a transient event, a firecracker explosion, lasting approximately 0.12 s is presented. Spectral results of the explosion show potassium and sodium emission lines present during the explosion and an absorption feature as the fireball extinguishes. Spatial and spectral reconstruction of a scene in which an explosion occurs during the middle of the collection period is also presented in the Experimental Results and Analysis section of this paper

Bond-Selective Intensity Diffraction Tomography

Recovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 seconds per volume, with a lateral and axial resolution of ~350 nm and ~1.1 micron, respectively. BS-IDT's application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 micron X 100 micron)

Tomographic Laser Absorption Imaging of Combustion Gases in the Mid-wave Infrared

This dissertation describes advancements in mid-infrared laser absorption tomography for spatio-temporal measurements of thermochemistry in reacting flows relevant to combustion systems. Tunable laser absorption spectroscopy is combined with tomographic reconstruction techniques to resolve small diameter ( < 1 cm) non-uniform flow fields with steep spatial gradients, leveraging emerging mid-wave infrared photonics. Multiple novel measurement methods, hardware configurations, and image processing techniques were investigated. Initially, a mid-infrared laser absorption tomography sensing method was developed for quantitative measurement of CO and CO2 concentrations and temperature distributions in turbulent premixed jet flames using a translation-stage-mounted optical system. This sensing approach was used to examine effects of varying fuel structure on carbon oxidation over a range of Reynolds number regimes. It was found that spatial and temporal resolution is limited in this method due to the finite laser beam size (~ 1 mm) and the slow mechanical translation of the optical system. To address these limitations, a novel laser absorption imaging (LAI) technique, that expands a single laser beam and replaces the detector with a high-speed infrared camera, was introduced to achieve enhanced spatial and temporal resolution for thermo-chemical imaging. As a demonstration of this new technique, distributions of combustion species were imaged in both axisymmetric and non-axisymmetric flow fields using linear tomography algorithms. For non-axisymetric flows, the limited view tomography problem often results in a blurring effect and artifacts in the reconstructed flow-field. In an effort to address these issues, state-of-the-art deep learning neural networks were developed and applied to solve the limited angle inversion. Initial results suggest that deep neural networks have potential to more accurately predict flame structures with fewer projection angles than linear tomography. This work provides a foundation for a new approach to quantitative time-resolved 3D thermo-chemical imaging in high-temperature reacting flows

The spectral X-ray imaging data acquisition (SpeXIDAQ) framework

Photon counting X-ray imagers have found their way into the mainstream scientific community in recent years, and have become important components in many scientific setups. These camera systems are in active development, with output data rates increasing significantly with every new generation of devices. A different class of PCD (Photon Counting Detector) devices has become generally available, where camera data output is no longer a matrix of photon counts but instead direct measurements of the deposited charge per pixel in every frame, which requires significant off-camera processing. This type of PCD, called a hyperspectral X-ray camera due to its fully spectroscopic output, yet again increases the demands put on the acquisition and processing backend. Not only are bandwidth requirements increased, but the need to do extensive data processing is also introduced with these hyperspectral PCD devices. To cope with these new developments the Spectral X-ray Imaging Data Acquisition framework (SpeXIDAQ) has been developed. All aspects of the imaging pipeline are handled by the SpeXIDAQ framework: from detector control and frame grabbing, to processing, storage and live visualisation during experiments

X-ray physico-chemical imaging during activation of cobalt-based Fischer-Tropsch synthesis catalysts

The imaging of catalysts and other functional materials under reaction conditions has advanced significantly in recent years. The combination of the computed tomography (CT) approach with methods such as X-ray diffraction (XRD), X-ray fluorescence (XRF) and X-ray absorption near-edge spectroscopy (XANES) now enables local chemical and physical state information to be extracted from within the interiors of intact materials which are, by accident or design, inhomogeneous. In this work, we follow the phase evolution during the initial reduction step(s) to form Co metal, for Co-containing particles employed as Fischer–Tropsch synthesis (FTS) catalysts; firstly, working at small length scales (approx. micrometre spatial resolution), a combination of sample size and density allows for transmission of comparatively low energy signals enabling the recording of ‘multimodal’ tomography, i.e. simultaneous XRF–CT, XANES–CT and XRD–CT. Subsequently, we show high-energy XRD–CT can be employed to reveal extent of reduction and uniformity of crystallite size on millimetre-sized TiO2 trilobes. In both studies, the CoO phase is seen to persist or else evolve under particular operating conditions and we speculate as to why this is observed