Publications

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Here, the ubiquity of computer processing power has enabled new imaging architectures that significantly depart from traditional imaging devices. Imaging systems with deeply enmeshed algorithmic elements are known as computational imaging systems, and can take unconventional physical forms compared to photographic systems. We report on the development and evaluation of a lensless imaging system utilizing an additively manufactured transparent optical element capable of producing image reconstructions after a calibration process. A generalized metric for image quality is presented and used to evaluate system performance as a function of total samples used to calibrate and test.

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We report on the design of a refracting prism array element for use in a computational lensless imaging system. The technique discussed enables creation of a refracting element that maximizes signal on a detector region.

We report on the design of a refracting prism array for use in a computational lensless imaging system. The technique discussed enables creation of a refracting element that maximizes signal on a detector region. Examples of pseudo-random prism arrays for the generation of images are provided. The pseudo-random prism array is compared to a randomly oriented prism array and the advantages of the optimal scattering element are highlighted.

The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.

Lensless imaging systems have the potential to provide new capabilities for lower size and weight configuration than traditional imaging systems. Lensless imagers frequently utilize computational imaging techniques, which moves the complexity of the system away from optical subcomponents and into a calibration process whereby the measurement matrix is estimated. We report on the design, simulation, and prototyping of a lensless imaging system that utilizes a 3D printed optically transparent random scattering element. Development of end-to-end system simulations, which includes simulations of the calibration process, as well as the data processing algorithm used to generate an image from the raw data are presented. These simulations utilize GPU-based raytracing software, and parallelized minimization algorithms to bring complete system simulation times down to the order of seconds. Hardware prototype results are presented, and practical lessons such as the effect of sensor noise on reconstructed image quality are discussed. System performance metrics are proposed and evaluated to discuss image quality in a manner that is relatable to traditional image quality metrics. Various hardware instantiations are discussed.

The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.

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Computational imagers fundamentally enable new optical hardware through the use of both physical and algorithmic elements. We report on the creation of a static lensless computational imaging system enabled by this paradigm.

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We have developed a four-channel optically pumped atomic magnetometer for magnetoencephalography (MEG) that incorporates a passive diffractive optical element (DOE). The DOE allows us to achieve a long, 18-mm gradiometer baseline in a compact footprint on the head. Using gradiometry, the sensitivities of the channels are < 5 fT/Hz1/2, and the 3-dB bandwidths are approximately 90 Hz, which are both sufficient to perform MEG. Additionally, the channels are highly uniform, which offers the possibility of employing standard MEG post-processing techniques. This module will serve as a building block of an array for magnetic source localization.

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The goal of this SAND report is to provide guidance for other groups hosting workshops and peerto-peer learning events at Sandia. Thus this SAND report provides detail about our team structure, how we brainstormed workshop topics and developed the workshop structure. A Workshop “Nuts and Bolts” section provides our timeline and check-list for workshop activities. The survey section provides examples of the questions we asked and how we adapted the workshop in response to the feedback.

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Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.