Optics Commons^™

Electromagnetic Multi–Gaussian Speckle, Milo W. Hyde Iv, Olga Korotkova

Faculty Publications

Generalizing our prior work on scalar multi-Gaussian (MG) distributed optical fields, we introduce the two-dimensional instantaneous electric-field vector whose components are jointly MG distributed. We then derive the single-point Stokes parameter probability density functions (PDFs) of MG-distributed light having an arbitrary degree and state of polarization. We show, in particular, that the intensity contrast of such a field can be tuned to values smaller or larger than unity. We validate our analysis by generating an example partially polarized MG field with a specified single-point polarization matrix using two different Monte Carlo simulation methods. We then compute the joint PDFs of …

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …

Enhanced Study Of Complex Systems By Unveiling Hidden Symmetries With Dynamical Visibility, Nhat Vu Minh Nguyen

2022 Symposium

One of the great challenges in complex and chaotic dynamics is to reveal its deterministic structures. These temporal dynamical structures are sometimes a consequence of hidden symmetries. Detecting and understanding them can allow the study of complex systems even without knowing the full underlying mathematical description of the system. Here we introduce a new technique, called Dynamical Visibility, that quantifies temporal correlations of the dynamics based upon some symmetry conditions. This visibility measures the departure of the dynamics from internal symmetries. We apply this technique to well-known chaotic systems, such as the logistic map and the circle map, as well …

Photophysics Of Metalloporphyrins Strongly Coupled To Cavity Photons, Aleksandr Avramenko

Wayne State University Dissertations

This dissertation will discuss the photophysics of metalloporphyrins, mainly CuTPP, ZnTPP, and H2TPP under strong light-matter coupling conditions. Strong light-matter coupling was achieved by embedding the previously mentioned chromophores into a spun coated PMMA polymer coating which is then incorporated as a spacer layer in a FabryPérot nano-cavity. The cavity thickness is chosen so that the cavity photon is of similar energy as the B, or Soret transition (2nd excited state) of the porphyrin molecule. The exchange of energy between the cavity photon and the molecular mode leads to the formation of polariton states.

Increasing the concentration of the molecules …

Machine Learning In Fiber Optics, Xiaowen Hu

Electronic Theses and Dissertations, 2020-2023

Recent burgeoning machine learning has revolutionized our ways of looking at the world. Being extraordinarily good at pattern recognition, machine learning has been widely applied to many fields to solve challenging problems. This dissertation demonstrates the applications of machine learning on scanning-free fiber-optic imaging systems (FOISs), and on the design of anti-resonant fibers. In the first part, we propose a semi-supervised learning framework called the adaptive inverse mapping (AIP) to stabilize the imaging performance through multimode fibers (MMFs). We show that if the state of the MMF is traced closely, the output images can be used as probes to correct …

Volume Bragg Gratings With Complex Phase Structures: A Three-Dimensional Foundation For Laser-Beam Engineering, Lam Mach

Electronic Theses and Dissertations, 2020-2023

Bragg diffraction is a natural phenomenon that arises from the coherent interference of scattered waves in multilayer structures with a well-defined periodicity. In practice, the physical size of these multilayer structures varies depending on the intended application, from micrometer-thick dielectric mirrors with tens of layers to centimeter-long Bragg gratings with ten-thousands of layers. The scope of this work centers around a unique class of multilayer elements developed in bulk photo-thermo-refractive (PTR) glass – the volume Bragg grating (VBG). The content of this thesis places an emphasis on the volume nature of these Bragg devices, implying a three-dimensional structure whereupon arbitrary …

A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, the worldwide temperature increase has resulted in rapid deglaciation and a higher risk of glacier-related natural hazards such as flooding and debris flow. Due to the severity of these hazards, continuous observation and detailed analysis of glacier fluctuations are crucial. Many such analyses require an accurately delineated glacier boundary. However, the complexity and heterogeneity of glaciers, particularly debris-covered glaciers (DCGs), poses a challenge for glacier mapping when using conventional remote sensing or machine-learning techniques. Some examples exist about small-scale automated glacier mapping, but large or regional-scale mapping is challenging. Previously, a deep-learning-based approach named GlacierNet2 had been …

Uncooled Microbolometer Imaging Systems For Machine Vision, Robert Grimming

Electronic Theses and Dissertations, 2020-2023

Over the last 20 years, the cost of uncooled microbolometer-based imaging systems has drastically decreased while performance has increased. In the simplest terms, the figure of merit for these types of thermal detectors is given in terms of the τ-NETD product, the combination of the thermal time constant and the noise equivalent temperature difference. Considering these factors, optimal system design parameters are investigated to maximize visual information content. This dissertation focuses on improving scene information in the longwave infrared (LWIR) spectrum that has had its validity and quality degraded by noise, blur, and reflected radiance. Taken together, noise and blur …

Patterned Liquid Crystal Devices For Near-Eye Displays, Kun Yin

Electronic Theses and Dissertations, 2020-2023

As a promising next-generation display, augmented reality (AR) and virtual reality (VR) have shown attractive features and attracted broad interests from both academia and industry. Currently, these near-eye displays (NEDs) have enabled numerous applications, ranging from education, medical, entertainment, to engineering, with the help of compact and functional patterned liquid crystal (LC) devices. The interplay between LC patterns and NEDs stimulates the development of novel LC devices with unique surface alignments and volume structures, which in turn feedback to achieve more compact and versatile NEDs. This dissertation will focus on the patterned LC with applications in NEDs. Firstly, we propose …

Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong

Electronic Theses and Dissertations, 2020-2023

Liquid crystal planar optics (LCPO) with versatile functionalities is emerging as a promising candidate for overcoming various challenges in near-eye displays, like augmented reality (AR) and virtual reality (VR), while maintaining a small form factor. This type of novel optical element exhibits unique properties, such as high efficiency, large angular/spectral bandwidths, polarization selectivity, and dynamic modulation. The basic molecular configuration of these novel reflective LCPO is analyzed, based on the simulation of molecular dynamics. In contrast to previously assumed planar-twist structure, our analysis predicts a slanted helix structure, which agrees with the measured results. The optical simulation model is established …

Development Of Holographic Phase Masks For Wavefront Shaping, Nafiseh Mohammadian

Electronic Theses and Dissertations, 2020-2023

This dissertation explores a new method for creating holographic phase masks (HPMs), which are phase transforming optical elements holographically recorded in photosensitive glass. This novel hologram recording method allows for the fast production of HPMs of any complexity, as opposed to the traditional multistep process, which includes the design and fabrication of a master phase mask operating in the UV region before the holographic recording step. We holographically recorded transmissive HPMs that are physically robust (they are recorded in a silicate glass volume), can handle tens of kilowatts of continuous wave (CW) laser power, are un-erasable, user defined, require no …

The Aquatic Particle Number Quandry, Alexander B. Bochdansky, Huanqing Huang, Maureen H. Conte

OES Faculty Publications

Optical surveys of aquatic particles and their particle size spectra have become important tools in studies of light propagation in water, classification of water masses, and the dynamics of trophic interactions affecting particle aggregation and flux. Here, we demonstrate that typical settings used in image analysis vastly underestimate particle numbers due to the particle – gel continuum. Applying a wide range of threshold values to change the sensitivity of our detection system, we show that macrogels cannot be separated from more dense particles, and that a true particle number per volume cannot be ascertained; only relative numbers in relation to …

Vertical Artifacts In High-Resolution Worldview-2 And Worldview-3 Satellite Imagery Of Aquatic Systems, Megan M. Coffer, Peter J. Whitman, Blake A. Schaeffer, Victoria Hill, Richard C. Zimmerman, Wilson B. Salls, Marie C. Lebrasse, David D. Graybill

OES Faculty Publications

Satellite image artefacts are features that appear in an image but not in the original imaged object and can negatively impact the interpretation of satellite data. Vertical artefacts are linear features oriented in the along-track direction of an image system and can present as either banding or striping; banding are features with a consistent width, and striping are features with inconsistent widths. This study used high-resolution data from DigitalGlobeʻs (now Maxar) WorldView-3 satellite collected at Lake Okeechobee, Florida (FL), on 30 August 2017. This study investigated the impact of vertical artefacts on both at-sensor radiance and a spectral index for …

Normative Data On The Foveal Avascular Zone In A Young Healthy Irish Population Using Optical Coherence Tomography Angiography, Susan M. O'Shea, Veronica O'Dwyer, Grainne Scanlon

Articles

Purpose: To establish normative data on the size, shape and vascular profile of the foveal avascular zone (FAZ) in a young, healthy, Irish population, using the Cirrus 5000 HD-OCT. Certain diseases may alter FAZ appearance. Normative databases provide normal baseline values for comparison, thus improving diagnostic ability.

Methods: One hundred and fifty-four subjects aged 18–35 years old were recruited. Superficial FAZ area, diameter, circularity, ganglion cell layer, central macular thickness (CMT), vascular perfusion and density were measured using the Cirrus 5000. Axial length was measured with the IOL Master and blood pressure was measured using the Omron sphygmomanometer. …

A Novel Phase And Spectroscopic Imaging Technique To Evaluate Cellular Functions, Ting Chean Khoo

Legacy Theses & Dissertations (2009 - 2024)

This thesis presents the application of Raman spectroscopy, digital holographic microscope (DHM) and transport intensity equation (TIE) in imaging biological samples. Raman spectroscopy is a non-destructive technique that can provide chemical structure, concentration, temperature, and molecular interactions. On the other hand, DHM and TIE provide physical measurements such as height, width, area and volume.We applied Raman spectroscopy to study iron-bound transferrin (Tf) in intact human breast cancer cells. Iron is an essential element required for human life and is highly regulated in the body. As the exact mechanisms of iron-bound Tf in cells are not well known, we developed a …

System Measurements For X-Ray Phase And Diffraction Imaging, Erik Wolfgang Tripi

Legacy Theses & Dissertations (2009 - 2024)

In medical imaging, X rays are used to look inside the body to find fractures in bones, abnormal masses, cavities in teeth, and so on. What makes X rays so good at looking at these types of structures is the X ray’s penetration power. When imaging soft tissue to search for tumors, X-ray images tend to have difficulty performing well. The reason for this is that the background structures, such as fat or fibro glandular tissue have similar absorption coefficients as the tumor. Mammography tends to have a high false positive rate and can miss tumors entirely as well. There …

First And Third Order Susceptibility Of Organic Molecules, Hao-Jung Chang

Electronic Theses and Dissertations, 2020-2023

Illuminating a material with intense laser excitation may change its properties and result in nonlinear absorption (NLA) and nonlinear refraction (NLR). In this dissertation we study the nonlinear absorption of organic compounds, the effect of extremely nondegenerate NLR in semiconductors, and the linear refractive index of organic solvents. In liquids, the refractive index has been studied for decades and different kinds of refractometers have been proposed. However, most of the reported values are in the visible region and only for commonly used solvents. We proposed a new interferometer-based refractometer that allows us to measure the refractive index from the visible …

Compact Lens Technologies: Curved Image Sensor And Volumetric Imaging Efficiency, Zhao Ma

Electronic Theses and Dissertations, 2020-2023

Compact image systems bring up people's attention in the field of target recognition, surveillance, situation awareness or even photography. Conventional metrics assess image system based on image quality without considering systems' volume. More comprehensive metrics, such as General Image-Quality Equation and the Targeting Task Performance metric, incorporates all image system components from object, lenses to detector and even imaging processing algorithm. All these key factors prohibit these metrics from being applied to image system in a convenient manner. Here, we propose a simple metric, volumetric imaging efficiency, considering both image quality and volume. Only concentrate on optical lenses enables the …

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan

Electrical and Computer Engineering Faculty Publications

Spiking neural network hardware offers a high performance, power-efficient and robust platform for the processing of complex data. Many of these systems require supervised learning, which poses a challenge when using gradient-based algorithms due to the discontinuous properties of SNNs. Memristor based hardware can offer gains in portability, power reduction, and throughput efficiency when compared to pure CMOS. This paper proposes a memristor-based spiking liquid state machine (LSM). The inherent dynamics of the LSM permit the use of supervised learning without backpropagation for weight updates. To carry out the design space evaluation of the LSM for optimal hardware performance, several …