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Dive into the research topics where Charles F. LaCasse is active.

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Featured researches published by Charles F. LaCasse.


Polarization: Measurement, Analysis, and Remote Sensing XII | 2016

Channeled spectropolarimetry using iterative reconstruction

Dennis J. Lee; Charles F. LaCasse; Julia M. Craven

Channeled spectropolarimeters (CSP) measure the polarization state of light as a function of wavelength. Conventional Fourier reconstruction suffers from noise, assumes the channels are band-limited, and requires uniformly spaced samples. To address these problems, we propose an iterative reconstruction algorithm. We develop a mathematical model of CSP measurements and minimize a cost function based on this model. We simulate a measured spectrum using example Stokes parameters, from which we compare conventional Fourier reconstruction and iterative reconstruction. Importantly, our iterative approach can reconstruct signals that contain more bandwidth, an advancement over Fourier reconstruction. Our results also show that iterative reconstruction mitigates noise effects, processes non-uniformly spaced samples without interpolation, and more faithfully recovers the ground truth Stokes parameters. This work offers a significant improvement to Fourier reconstruction for channeled spectropolarimetry.


Optics and Photonics for Information Processing XII | 2018

Optical systems for task-specific compressive classification

Gabriel C. Birch; Tu-Thach Quach; Meghan Galiardi; Amber L. Dagel; Charles F. LaCasse

Advancements in machine learning (ML) and deep learning (DL) have enabled imaging systems to perform complex classification tasks, opening numerous problem domains to solutions driven by high quality imagers coupled with algorithmic elements. However, current ML and DL methods for target classification typically rely upon algorithms applied to data measured by traditional imagers. This design paradigm fails to enable the ML and DL algorithms to influence the sensing device itself, and treats the optimization of the sensor and algorithm as separate sequential elements. Additionally, this current paradigm narrowly investigates traditional images, and therefore traditional imaging hardware, as the primary means of data collection. We investigate alternative architectures for computational imaging systems optimized for specific classification tasks, such as digit classification. This involves a holistic approach to the design of the system from the imaging hardware to algorithms. Techniques to find optimal compressive representations of training data are discussed, and most-useful object-space information is evaluated. Methods to translate task-specific compressed data representations into non-traditional computational imaging hardware are described, followed by simulations of such imaging devices coupled with algorithmic classification using ML and DL techniques. Our approach allows for inexpensive, efficient sensing systems. Reduced storage and bandwidth are achievable as well since data representations are compressed measurements which is especially important for high data volume systems.


international carnahan conference on security technology | 2017

Computational optical physical unclonable functions

Gabriel C. Birch; Bryana L. Woo; Charles F. LaCasse; Jaclynn J. Stubbs; Amber L. Dagel

Physical unclonable functions (PUFs) are devices which are easily probed but difficult to predict. Optical PUFs have been discussed within the literature, with traditional optical PUFs typically using spatial light modulators, coherent illumination, and scattering volumes; however, these systems can be large, expensive, and difficult to maintain alignment in practical conditions. We propose and demonstrate a new kind of optical PUF based on computational imaging and compressive sensing to address these challenges with traditional optical PUFs. This work describes the design, simulation, and prototyping of this computational optical PUF (COPUF) that utilizes incoherent polychromatic illumination passing through an additively manufactured refracting optical polymer element. We demonstrate the ability to pass information through a COPUF using a variety of sampling methods, including the use of compressive sensing. The sensitivity of the COPUF system is also explored. We explore non-traditional PUF configurations enabled by the COPUF architecture. The double COPUF system, which employees two serially connected COPUFs, is proposed and analyzed as a means to authenticate and communicate between two entities that have previously agreed to communicate. This configuration enables estimation of a message inversion key without the calculation of individual COPUF inversion keys at any point in the PUF life cycle. Our results show that it is possible to construct inexpensive optical PUFs using computational imaging. This could lead to new uses of PUFs in places where electrical PUFs cannot be utilized effectively, as low cost tags and seals, and potentially as authenticating and communicating devices.


SPIE Commercial + Scientific Sensing and Imaging | 2017

Lensless computational imaging using 3D printed transparent elements

Gabriel C. Birch; Charles F. LaCasse; Amber L. Dagel; Bryana L. Woo

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.


Optical Engineering | 2017

Field deployable pushbroom hyperspectral imaging polarimeter

Michael W. Kudenov; Mariano Lowenstern; Julia M. Craven; Charles F. LaCasse

Abstract. Hyperspectral imaging polarimetry enables both the spectrum and its spectrally resolved state of polarization to be measured. This information is important for identifying material properties for various applications in remote sensing and agricultural monitoring. We describe the design and performance of a ruggedized, field deployable hyperspectral imaging polarimeter, designed for wavelengths spanning the visible to near-infrared (450 to 800 nm). An entrance slit was used to sample the scene in a pushbroom scanning mode across a 30 deg vertical by 110 deg horizontal field-of-view. Furthermore, athermalized achromatic retarders were implemented in a channel spectrum generator to measure the linear Stokes parameters. The mechanical and optical layout of the system and its peripherals, in addition to the results of the sensor’s spectral and polarimetric calibration, are provided. Finally, field measurements are also provided and an error analysis is conducted. With its present calibration, the sensor has an absolute polarimetric error of 2.5% RMS and a relative spectral error of 2.3% RMS.


Proceedings of SPIE | 2016

Ideal system morphology and reflectivity measurements for model development and validation

Thomas J. Kulp; Ricky Sommers; Karen Lee Krafcik; B. E. Mills; Thomas A. Reichardt; J. K. Dorrance; Charles F. LaCasse; K. H. Fuerschbach; Julia M. Craven

This paper describes measurements being made on a series of material systems for the purpose of developing a radiative-transfer model that describes the reflectance of light by granular solids. It is well recognized that the reflectance spectra of granular materials depend on their intrinsic (n(λ) and k(λ)) and extrinsic (morphological) properties. There is, however, a lack of robust and proven models to relate spectra to these parameters. The described work is being conducted in parallel with a modeling effort1 to address this need. Each follows a common developmental spiral in which material properties are varied and the ability of the model to calculate the effects of the changes are tested. The parameters being varied include particle size/shape, packing density, material birefringence, optical thickness, and spectral contribution of a substrate. It is expected that the outcome of this work will be useful in interpreting reflectance data for hyperspectral imaging (HSI), and for a variety of other areas that rely on it.


Polarization: Measurement, Analysis, and Remote Sensing XII | 2016

Maximum bandwidth snapshot channeled imaging polarimeter with polarization gratings

Charles F. LaCasse; Brian J. Redman; Michael W. Kudenov; Julia M. Craven

Compact snapshot imaging polarimeters have been demonstrated in literature to provide Stokes parameter estimations for spatially varying scenes using polarization gratings. However, the demonstrated system does not employ aggressive modulation frequencies to take full advantage of the bandwidth available to the focal plane array. A snapshot imaging Stokes polarimeter is described and demonstrated through results. The simulation studies the challenges of using a maximum bandwidth configuration for a snapshot polarization grating based polarimeter, such as the fringe contrast attenuation that results from higher modulation frequencies. Similar simulation results are generated and compared for a microgrid polarimeter. Microgrid polarimeters are instruments where pixelated polarizers are superimposed onto a focal plan array, and this is another type of spatially modulated polarimeter, and the most common design uses a 2x2 super pixel of polarizers which maximally uses the available bandwidth of the focal plane array.


Proceedings of SPIE | 2015

A polarization system for persistent chemical detection

Julia Craven-Jones; Leah N. Appelhans; Eric Couphos; Todd J. Embree; Patrick Sean Finnegan; Dennis H. Goldstein; David B. Karelitz; Charles F. LaCasse; Ting S. Luk; Adoum Mahamat; Lee Massey; Anthony Tanbakuchi; Cody M. Washburn; Steven R. Vigil

We report on the development of a prototype polarization tag based system for detecting chemical vapors. The system primarily consists of two components, a chemically sensitive tag that experiences a change in its optical polarization properties when exposed to a specific chemical of interest, and an optical imaging polarimeter that is used to measure the polarization properties of the tags. Although the system concept could be extended to other chemicals, for the initial system prototype presented here the tags were developed to be sensitive to hydrogen fluoride (HF) vapors. HF is used in many industrial processes but is highly toxic and thus monitoring for its presence and concentration is often of interest for personnel and environmental safety. The tags are periodic multilayer structures that are produced using standard photolithographic processes. The polarimetric imager has been designed to measure the degree of linear polarization reflected from the tags in the short wave infrared. By monitoring the change in the reflected polarization signature from the tags, the polarimeter can be used to determine if the tag was exposed to HF gas. In this paper, a review of the system development effort and preliminary test results are presented and discussed, as well as our plan for future work.


Optical Design and Fabrication 2017 (Freeform, IODC, OFT) (2017), paper ITu1A.5 | 2017

Tolerance analysis through computational imaging simulations

Gabriel C. Birch; Charles F. LaCasse; Jaclynn J. Stubbs; Amber L. Dagel; Jon Bradley


Optical Design and Fabrication 2017 (Freeform, IODC, OFT) (2017), paper ITh4A.6 | 2017

Static lensless random scattering imagers via 3D printing

Charles F. LaCasse; Gabriel C. Birch; Amber L. Dagel; Bryana L. Woo

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Amber L. Dagel

Sandia National Laboratories

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Gabriel C. Birch

Sandia National Laboratories

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Bryana L. Woo

Sandia National Laboratories

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Jaclynn J. Stubbs

Sandia National Laboratories

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Michael W. Kudenov

North Carolina State University

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Anthony Tanbakuchi

Sandia National Laboratories

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B. E. Mills

Sandia National Laboratories

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Brian J. Redman

North Carolina State University

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