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Harnessing Spatial Intensity Fluctuations for Optical Imaging and Sensing
Title
Harnessing Spatial Intensity Fluctuations for Optical Imaging and Sensing.
Creator
Akhlaghi Bouzan, Milad, Dogariu, Aristide, Saleh, Bahaa, Pang, Sean, Atia, George, University of Central Florida
Abstract / Description
Properties of light such as amplitude and phase, temporal and spatial coherence, polarization, etc. are abundantly used for sensing and imaging. Regardless of the passive or active nature of the sensing method, optical intensity fluctuations are always present! While these fluctuations are usually regarded as noise, there are situations where one can harness the intensity fluctuations to enhance certain attributes of the sensing procedure. In this thesis, we developed different sensing...
Show moreProperties of light such as amplitude and phase, temporal and spatial coherence, polarization, etc. are abundantly used for sensing and imaging. Regardless of the passive or active nature of the sensing method, optical intensity fluctuations are always present! While these fluctuations are usually regarded as noise, there are situations where one can harness the intensity fluctuations to enhance certain attributes of the sensing procedure. In this thesis, we developed different sensing methodologies that use statistical properties of optical fluctuations for gauging specific information. We examine this concept in the context of three different aspects of computational optical imaging and sensing. First, we study imposing specific statistical properties to the probing field to image or characterize certain properties of an object through a statistical analysis of the spatially integrated scattered intensity. This offers unique capabilities for imaging and sensing techniques operating in highly perturbed environments and low-light conditions. Next, we examine optical sensing in the presence of strong perturbations that preclude any controllable field modification. We demonstrate that inherent properties of diffused coherent fields and fluctuations of integrated intensity can be used to track objects hidden behind obscurants. Finally, we address situations where, due to coherent noise, image accuracy is severely degraded by intensity fluctuations. By taking advantage of the spatial coherence properties of optical fields, we show that this limitation can be effectively mitigated and that a significant improvement in the signal-to-noise ratio can be achieved even in one single-shot measurement. The findings included in this dissertation illustrate different circumstances where optical fluctuations can affect the efficacy of computational optical imaging and sensing. A broad range of applications, including biomedical imaging and remote sensing, could benefit from the new approaches to suppress, enhance, and exploit optical fluctuations, which are described in this dissertation.
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Date Issued
2017
Identifier
CFE0007274, ucf:52200
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007274
Computational imaging systems for high-speed, adaptive sensing applications
Title
Computational imaging systems for high-speed, adaptive sensing applications.
Creator
Sun, Yangyang, Pang, Sean, Li, Guifang, Schulzgen, Axel, Pensky, Marianna, University of Central Florida
Abstract / Description
Driven by the advances in signal processing and ubiquitous availability of high-speed low-cost computing resources over the past decade, computational imaging has seen the growing interest. Improvements on spatial, temporal, and spectral resolutions have been made with novel designs of imaging systems and optimization methods. However, there are two limitations in computational imaging. 1), Computational imaging requires full knowledge and representation of the imaging system called the...
Show moreDriven by the advances in signal processing and ubiquitous availability of high-speed low-cost computing resources over the past decade, computational imaging has seen the growing interest. Improvements on spatial, temporal, and spectral resolutions have been made with novel designs of imaging systems and optimization methods. However, there are two limitations in computational imaging. 1), Computational imaging requires full knowledge and representation of the imaging system called the forward model to reconstruct the object of interest. This limits the applications in the systems with a parameterized unknown forward model such as range imaging systems. 2), the regularization in the optimization process incorporates strong assumptions which may not accurately reflect the a priori distribution of the object. To overcome these limitations, we propose 1) novel optimization frameworks for applying computational imaging on active and passive range imaging systems and achieve 5-10 folds improvement on temporal resolution in various range imaging systems; 2) a data-driven method for estimating the distribution of high dimensional objects and a framework of adaptive sensing for maximum information gain. The adaptive strategy with our proposed method outperforms Gaussian process-based method consistently. The work would potentially benefit high-speed 3D imaging applications such as autonomous driving and adaptive sensing applications such as low-dose adaptive computed tomography(CT).
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Date Issued
2019
Identifier
CFE0007867, ucf:52784
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007867
The Formation and Characterization of Mesoscopic J- and H-aggregates with Controlled Morphologies by the Co- and Templated Assembly of Cyanine Dyes
Title
The Formation and Characterization of Mesoscopic J- and H-aggregates with Controlled Morphologies by the Co- and Templated Assembly of Cyanine Dyes.
Creator
Rhodes, Samuel, Fang, Jiyu, Jiang, Tengfei, Dong, Yajie, Florczyk, Stephen, Pang, Sean, University of Central Florida
Abstract / Description
The supramolecular aggregates of ?-conjugated molecules have become an area of great interest to the scientific community in recent years for their promise in biosensors and optoelectronic devices. Among various supramolecular aggregates, J- and H-aggregates of ?-conjugated dye molecules are particularly interesting because of their unique optical and excitonic properties that are not given by individual molecules. H-aggregates are composed of dye molecules in a face-to-face stacking, giving...
Show moreThe supramolecular aggregates of ?-conjugated molecules have become an area of great interest to the scientific community in recent years for their promise in biosensors and optoelectronic devices. Among various supramolecular aggregates, J- and H-aggregates of ?-conjugated dye molecules are particularly interesting because of their unique optical and excitonic properties that are not given by individual molecules. H-aggregates are composed of dye molecules in a face-to-face stacking, giving rise to a blue-shifted absorption band compared with the monomer band and a strong emission quenching. In contrast, J-aggregates represent an edge-to-edge stacking of dye molecules, showing a red-shifted absorption band with respect to the monomer band and a strong fluorescence emission. However, the use of J- and H-aggregates in biosensors and optoelectronic devices remains a challenge because of the difficulty of controlling their sizes and morphologies. In this dissertation, we develop two different paths for controlling the size and morphology of J- and H-aggregates. First, we show that the co-assembly of cyanine dyes and lithocholic acid (LCA) in ammonia solution can lead to the formation of mesoscopic J- and H-aggregate fibers, depending on the condition under which the co-assembly occurs. Second, we report the formation of mesoscopic J-aggregate tubes by using the preformed LCA tubes as a template. The structure, optical, and electronic properties of these J- and H-aggregate fiber and tubes are studied as a function of temperature. Finally, we exploit their applications as photo-induced electron transfer supramolecular probes for the detection of dopamine, an important neurotransmitter in central and peripheral nervous systems.
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Date Issued
2018
Identifier
CFE0007412, ucf:52718
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007412
Imaging through Glass-air Anderson Localizing Optical Fiber
Title
Imaging through Glass-air Anderson Localizing Optical Fiber.
Creator
Zhao, Jian, Schulzgen, Axel, Amezcua Correa, Rodrigo, Pang, Sean, Delfyett, Peter, Mafi, Arash, University of Central Florida
Abstract / Description
The fiber-optic imaging system enables imaging deeply into hollow tissue tracts or organs of biological objects in a minimally invasive way, which are inaccessible to conventional microscopy. It is the key technology to visualize biological objects in biomedical research and clinical applications. The fiber-optic imaging system should be able to deliver a high-quality image to resolve the details of cell morphology in vivo and in real time with a miniaturized imaging unit. It also has to be...
Show moreThe fiber-optic imaging system enables imaging deeply into hollow tissue tracts or organs of biological objects in a minimally invasive way, which are inaccessible to conventional microscopy. It is the key technology to visualize biological objects in biomedical research and clinical applications. The fiber-optic imaging system should be able to deliver a high-quality image to resolve the details of cell morphology in vivo and in real time with a miniaturized imaging unit. It also has to be insensitive to environmental perturbations, such as mechanical bending or temperature variations. Besides, both coherent and incoherent light sources should be compatible with the imaging system. It is extremely challenging for current technologies to address all these issues simultaneously. The limitation mainly lies in the deficient stability and imaging capability of fiber-optic devices and the limited image reconstruction capability of algorithms. To address these limitations, we first develop the randomly disordered glass-air optical fiber featuring a high air-filling fraction (~28.5 %) and low loss (~1 dB per meter) at visible wavelengths. Due to the transverse Anderson localization effect, the randomly disordered structure can support thousands of modes, most of which demonstrate single-mode properties. By making use of these modes, the randomly disordered optical fiber provides a robust and low-loss imaging system which can transport images with higher quality than the best commercially available imaging fiber. We further demonstrate that deep-learning algorithm can be applied to the randomly disordered optical fiber to overcome the physical limitation of the fiber itself. At the initial stage, a laser-illuminated system is built by integrating a deep convolutional neural network with the randomly disordered optical fiber. Binary sparse objects, such as handwritten numbers and English letters, are collected, transported and reconstructed using this system. It is proved that this first deep-learning-based fiber imaging system can perform artifact-free, lensless and bending-independent imaging at variable working distances. In real-world applications, the gray-scale biological subjects have much more complicated features. To image biological tissues, we re-design the architecture of the deep convolutional neural network and apply it to a newly designed system using incoherent illumination. The improved fiber imaging system has much higher resolution and faster reconstruction speed. We show that this new system can perform video-rate, artifact-free, lensless cell imaging. The cell imaging process is also remarkably robust with regard to mechanical bending and temperature variations. In addition, this system demonstrates stronger transfer-learning capability than existed deep-learning-based fiber imaging system.
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Date Issued
2019
Identifier
CFE0007746, ucf:52405
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007746
Spectral properties of the finite Hilbert transform on two adjacent intervals via the method of Riemann-Hilbert problem
Title
Spectral properties of the finite Hilbert transform on two adjacent intervals via the method of Riemann-Hilbert problem.
Creator
Blackstone, Elliot, Tovbis, Alexander, Katsevich, Alexander, Tamasan, Alexandru, Pang, Sean, University of Central Florida
Abstract / Description
In this dissertation, we study a self-adjoint integral operator $\hat{K}$ which is defined in terms of finite Hilbert transforms on two adjacent intervals. These types of transforms arise when one studies the interior problem of tomography. The operator $\hat{K}$ possesses a so-called ``integrable kernel'' and it is known that the spectral properties of $\hat{K}$ are intimately related to a $2\times2$ matrix function $\Gamma(z;\lambda)$ which is the solution to a particular Riemann-Hilbert...
Show moreIn this dissertation, we study a self-adjoint integral operator $\hat{K}$ which is defined in terms of finite Hilbert transforms on two adjacent intervals. These types of transforms arise when one studies the interior problem of tomography. The operator $\hat{K}$ possesses a so-called ``integrable kernel'' and it is known that the spectral properties of $\hat{K}$ are intimately related to a $2\times2$ matrix function $\Gamma(z;\lambda)$ which is the solution to a particular Riemann-Hilbert problem (in the $z$ plane). We express $\Gamma(z;\lambda)$ explicitly in terms of hypergeometric functions and find the small $\lambda$ asymptotics of $\Gamma(z;\lambda)$. This asymptotic analysis is necessary for the spectral analysis of the finite Hilbert transform on multiple adjacent intervals. We show that $\Gamma(z;\lambda)$ also has a jump in the $\lambda$ plane which allows us to compute the jump of the resolvent of $\hat{K}$. This jump is an important step in showing that the finite Hilbert transforms has simple and purely absolutely continuous spectrum. The well known spectral theory now allows us to construct unitary operators which diagonalize the finite Hilbert transforms. Lastly, we mention some future directions which include the many interval scenario and a bispectral property of $\hat{K}$.
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Date Issued
2019
Identifier
CFE0007602, ucf:52527
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007602