Current Search: Pang, Sean (x)
View All Items
 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 lowlight 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 signaltonoise ratio can be achieved even in one singleshot 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.
Show less  Date Issued
 2017
 Identifier
 CFE0007274, ucf:52200
 Format
 Document (PDF)
 PURL
 http://purl.flvc.org/ucf/fd/CFE0007274
 Title
 Computational imaging systems for highspeed, 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 highspeed lowcost 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 highspeed lowcost 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 510 folds improvement on temporal resolution in various range imaging systems; 2) a datadriven 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 processbased method consistently. The work would potentially benefit highspeed 3D imaging applications such as autonomous driving and adaptive sensing applications such as lowdose adaptive computed tomography(CT).
Show less  Date Issued
 2019
 Identifier
 CFE0007867, ucf:52784
 Format
 Document (PDF)
 PURL
 http://purl.flvc.org/ucf/fd/CFE0007867
 Title
 The Formation and Characterization of Mesoscopic J and Haggregates 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 Haggregates of ?conjugated dye molecules are particularly interesting because of their unique optical and excitonic properties that are not given by individual molecules. Haggregates are composed of dye molecules in a facetoface 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 Haggregates of ?conjugated dye molecules are particularly interesting because of their unique optical and excitonic properties that are not given by individual molecules. Haggregates are composed of dye molecules in a facetoface stacking, giving rise to a blueshifted absorption band compared with the monomer band and a strong emission quenching. In contrast, Jaggregates represent an edgetoedge stacking of dye molecules, showing a redshifted absorption band with respect to the monomer band and a strong fluorescence emission. However, the use of J and Haggregates 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 Haggregates. First, we show that the coassembly of cyanine dyes and lithocholic acid (LCA) in ammonia solution can lead to the formation of mesoscopic J and Haggregate fibers, depending on the condition under which the coassembly occurs. Second, we report the formation of mesoscopic Jaggregate tubes by using the preformed LCA tubes as a template. The structure, optical, and electronic properties of these J and Haggregate fiber and tubes are studied as a function of temperature. Finally, we exploit their applications as photoinduced electron transfer supramolecular probes for the detection of dopamine, an important neurotransmitter in central and peripheral nervous systems.
Show less  Date Issued
 2018
 Identifier
 CFE0007412, ucf:52718
 Format
 Document (PDF)
 PURL
 http://purl.flvc.org/ucf/fd/CFE0007412
 Title
 Imaging through Glassair 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 fiberoptic 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 fiberoptic imaging system should be able to deliver a highquality 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 fiberoptic 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 fiberoptic imaging system should be able to deliver a highquality 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 fiberoptic devices and the limited image reconstruction capability of algorithms. To address these limitations, we first develop the randomly disordered glassair optical fiber featuring a high airfilling 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 singlemode properties. By making use of these modes, the randomly disordered optical fiber provides a robust and lowloss imaging system which can transport images with higher quality than the best commercially available imaging fiber. We further demonstrate that deeplearning algorithm can be applied to the randomly disordered optical fiber to overcome the physical limitation of the fiber itself. At the initial stage, a laserilluminated 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 deeplearningbased fiber imaging system can perform artifactfree, lensless and bendingindependent imaging at variable working distances. In realworld applications, the grayscale biological subjects have much more complicated features. To image biological tissues, we redesign 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 videorate, artifactfree, 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 transferlearning capability than existed deeplearningbased fiber imaging system.
Show less  Date Issued
 2019
 Identifier
 CFE0007746, ucf:52405
 Format
 Document (PDF)
 PURL
 http://purl.flvc.org/ucf/fd/CFE0007746
 Title
 Spectral properties of the finite Hilbert transform on two adjacent intervals via the method of RiemannHilbert problem.
 Creator

Blackstone, Elliot, Tovbis, Alexander, Katsevich, Alexander, Tamasan, Alexandru, Pang, Sean, University of Central Florida
 Abstract / Description

In this dissertation, we study a selfadjoint 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 socalled ``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 RiemannHilbert...
Show moreIn this dissertation, we study a selfadjoint 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 socalled ``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 RiemannHilbert 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 $\hat{K}$.
Show less  Date Issued
 2019
 Identifier
 CFE0007602, ucf:52527
 Format
 Document (PDF)
 PURL
 http://purl.flvc.org/ucf/fd/CFE0007602