mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral tradeoff. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from an RGB image. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep-learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral tradeoff, offering simple hardware requirements and potential applications of various machine-learning techniques.Comment: This paper will appear in PNAS Nexu

Proceedings of the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

This book is a collection of 15 reviewed technical reports summarizing the presentations at the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. The covered topics include image processing, optical signal processing, visual inspection, pattern recognition and classification, human-machine interaction, world and situation modeling, autonomous system localization and mapping, information fusion, and trust propagation in sensor networks

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

An Insect-Inspired Target Tracking Mechanism for Autonomous Vehicles

Target tracking is a complicated task from an engineering perspective, especially where targets are small and seen against complex natural environments. Due to the high demand for robust target tracking algorithms a great deal of research has focused on this area. However, most engineering solutions developed for this purpose are often unreliable in real world conditions or too computationally expensive to be used in real-time applications. While engineering methods try to solve the problem of target detection and tracking by using high resolution input images, fast processors, with typically computationally expensive methods, a quick glance at nature provides evidence that practical real world solutions for target tracking exist. Many animals track targets for predation, territorial or mating purposes and with millions of years of evolution behind them, it seems reasonable to assume that these solutions are highly efficient. For instance, despite their low resolution compound eyes and tiny brains, many flying insects have evolved superb abilities to track targets in visual clutter even in the presence of other distracting stimuli, such as swarms of prey and conspecifics. The accessibility of the dragonfly for stable electrophysiological recordings makes this insect an ideal and tractable model system for investigating the neuronal correlates for complex tasks such as target pursuit. Studies on dragonflies identified and characterized a set of neurons likely to mediate target detection and pursuit referred to as ‘small target motion detector’ (STMD) neurons. These neurons are selective for tiny targets, are velocity-tuned, contrast-sensitive and respond robustly to targets even against the motion of background. These neurons have shown several high-order properties which can contribute to the dragonfly’s ability to robustly pursue prey with over a 97% success rate. These include the recent electrophysiological observations of response ‘facilitation’ (a slow build-up of response to targets that move on long, continuous trajectories) and ‘selective attention’, a competitive mechanism that selects one target from alternatives. In this thesis, I adopted a bio-inspired approach to develop a solution for the problem of target tracking and pursuit. Directly inspired by recent physiological breakthroughs in understanding the insect brain, I developed a closed-loop target tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. First, I tested this model in virtual world simulations using MATLAB/Simulink. The results of these simulations show robust performance of this insect-inspired model, achieving high prey capture success even within complex background clutter, low contrast and high relative speed of pursued prey. Additionally, these results show that inclusion of facilitation not only substantially improves success for even short-duration pursuits, it also enhances the ability to ‘attend’ to one target in the presence of distracters. This inspect-inspired system has a relatively simple image processing strategy compared to state-of-the-art trackers developed recently for computer vision applications. Traditional machine vision approaches incorporate elaborations to handle challenges and non-idealities in the natural environments such as local flicker and illumination changes, and non-smooth and non-linear target trajectories. Therefore, the question arises as whether this insect inspired tracker can match their performance when given similar challenges? I investigated this question by testing both the efficacy and efficiency of this insect-inspired model in open-loop, using a widely-used set of videos recorded under natural conditions. I directly compared the performance of this model with several state-of-the-art engineering algorithms using the same hardware, software environment and stimuli. This insect-inspired model exhibits robust performance in tracking small moving targets even in very challenging natural scenarios, outperforming the best of the engineered approaches. Furthermore, it operates more efficiently compared to the other approaches, in some cases dramatically so. Computer vision literature traditionally test target tracking algorithms only in open-loop. However, one of the main purposes for developing these algorithms is implementation in real-time robotic applications. Therefore, it is still unclear how these algorithms might perform in closed-loop real-world applications where inclusion of sensors and actuators on a physical robot results in additional latency which can affect the stability of the feedback process. Additionally, studies show that animals interact with the target by changing eye or body movements, which then modulate the visual inputs underlying the detection and selection task (via closed-loop feedback). This active vision system may be a key to exploiting visual information by the simple insect brain for complex tasks such as target tracking. Therefore, I implemented this insect-inspired model along with insect active vision in a robotic platform. I tested this robotic implementation both in indoor and outdoor environments against different challenges which exist in real-world conditions such as vibration, illumination variation, and distracting stimuli. The experimental results show that the robotic implementation is capable of handling these challenges and robustly pursuing a target even in highly challenging scenarios.Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 201

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Comprehensive retinal image analysis: image processing and feature extraction techniques oriented to the clinical task

Medical digital imaging has become a key element of modern health care procedures. It provides a visual documentation, a permanent record for the patients, and most importantly the ability to extract information about many diseases. Ophthalmology is a field that is heavily dependent on the analysis of digital images because they can aid in establishing an early diagnosis even before the first symptoms appear. This dissertation contributes to the digital analysis of such images and the problems that arise along the imaging pipeline, a field that is commonly referred to as retinal image analysis. We have dealt with and proposed solutions to problems that arise in retinal image acquisition and longitudinal monitoring of retinal disease evolution. Specifically, non-uniform illumination, poor image quality, automated focusing, and multichannel analysis. However, there are many unavoidable situations in which images of poor quality, like blurred retinal images because of aberrations in the eye, are acquired. To address this problem we have proposed two approaches for blind deconvolution of blurred retinal images. In the first approach, we consider the blur to be space-invariant and later in the second approach we extend the work and propose a more general space-variant scheme. For the development of the algorithms we have built preprocessing solutions that have enabled the extraction of retinal features of medical relevancy, like the segmentation of the optic disc and the detection and visualization of longitudinal structural changes in the retina. Encouraging experimental results carried out on real retinal images coming from the clinical setting demonstrate the applicability of our proposed solutions

Forecaster Warning Decision Making with Rapidly-Updating Radar Data

Phased-array radar is being considered as a potential future replacement technology for the current operational Weather Surveillance Radar 1988 Doppler system. One of the most notable differences in these weather radar systems is the temporal resolution. With phased-array radar collecting volumetric updates 4–6 times more frequently, the operational impacts of rapidly-updating radar data on forecasters’ warning decision processes must be assessed. The Phased Array Radar Innovative Sensing Experiment (PARISE) was therefore designed to examine forecasters’ warning performance and related warning decision processes during use of ~1-min radar updates in simulated real-time warning operation scenarios. While the 2010, 2012, and 2013 PARISE studies reported encouraging findings for forecasters’ use of these data, each of these studies were limited in terms of sample size and the chosen methods. Additionally, important research questions that had not yet been explored remained unanswered. To address these limitations and investigate new research questions, thirty National Weather Service forecasters were invited to the NOAA Hazardous Weather Testbed to participate in the 2015 PARISE. Participating forecasters completed three components of this study: 1) the traditional experiment, 2) an eye-tracking experiment, and 3) a focus group. The first component was designed to build on previous work by assessing and comparing forecasters’ warning performance and related cognitive workload when using 1-min, 2-min, and 5-min phased-array radar updates during simulated warning operations. This traditional experiment was comprised of nine weather events that varied in terms of weather threat. Next, forecasters’ eye movement data were observed as they each worked a single weather event with either 1-min or 5-min phased-array radar updates. This work was motivated by an eye-tracking pilot study, in which a forecaster’s eye movement data was found to correspond meaningfully to their retrospective recall data that described their warning decision process. The 2015 PARISE eye-tracking experiment allowed for an objective analysis of how forecasters interacted with a radar display and warning interface for a single weather event, and more specifically, supported an investigation of whether radar update speed impacts how forecasters distribute their attention. Lastly, six focus groups were conducted to enable forecasters to share their experiences on their use of rapidly-updating phased-array radar data during the experiment. The findings from the focus groups provide motivation for the integration of rapidly-updating radar data into the forecast office and highlight some important considerations for successful use of these data during warning operations. The work presented in this dissertation was approved by the University of Oklahoma’s Office of Human Research Participant Protection Institutional Review Board under projects #5226 and #5580

Bioreplicated Light-Harvesting Layers for Photovoltaics

Die hierarchischen Mikro-/Nanostrukturen, welche die Blütenblattoberflächen einer Vielzahl von Blütenpflanzen zieren, weisen oftmals hervorragende Lichtsammlungs- sowie Selbstreinigungseigenschaften auf. Diese Qualitäten können mit Hilfe von direkten Replikationsverfahren technisch nutzbar gemacht werden, beispielsweise für die photovoltaische Stromerzeugung. Replikationsverfahren zielen darauf ab die multi-skalige Oberflächenstruktur von Blütenblättern in ein transparentes Polymer zu übertragen und auf der Vorderseite von Solarmodulen aufzubringen. Im Laufe der letzten Jahren haben sich hauptsächlich Polymerabgüsse und die sog. Soft-Imprint Nanolithographie als gängige Verfahren zur direkten Kopie von (sowohl künstlich hergestellten, als auch) natürlichen Mikro-, Nano-, und multi-skaligen Strukturen in adäquate technische Materialien, wie z.B. Polymere zur Ausnutzung ihrer hochoptimierten optischen und/oder Benetzungseigenschaften für optoelektronische Bauteile, etabliert. Eine großflächige Anwendung dieser Verfahren wurde jedoch bislang aufgrund der naturgegebenen Maximalgröße von Blütenblättern nicht etabliert. Des Weiteren kann auf Basis eines einzigen Polymerstempel nur eine limitierte Anzahl an Replikaten mit hoher Strukturqualität mittels Soft-Imprint hergestellt werden. Ein Teil dieser Arbeit befasst sich mit der Überwindung dieser Hürden durch Weiterentwicklung der Replikationstechniken für pflanzliche Oberflächenstrukturen. Eine solche, in der Fläche hochskalierte Bioreplikationsmethode mit gleichzeitig erheblich gesteigertem Durchsatz wird in dieser Arbeit am Beispiel der hierarchischen Oberflächenstruktur von Rosenblütenblättern als natürliche Strukturvorlage aufgezeigt. Das vorgestellte Verfahren basiert auf der Entwicklung metallischer Prägewerkzeuge, welche in einem statischen Heißprägeprozess eingesetzt werden. Diese Entwicklung ermöglicht die Herstellung von Replikaten pflanzlicher Oberflächenstrukturen mit hoher Strukturqualität, in nie dagewesener Stückzahl, und erstmals auch in einer für eine Integration in kommerzielle Solarmodule relevanten Größe. Die hochskalierten, temperaturstabilen und mechanisch robusten Prägewerkzeuge werden dabei per galvanischer Nickelabscheidung hergestellt. Die primäre Strukturvorlage für diesen Prozess wird dabei durch vorsichtige Aneinanderreihung mehrerer natürlicher Rosenblütenblätter zu einer möglichst lücken- und nahtlos strukturierten Einheit erzeugt. Der Heißprägeprozess zur Herstellung hochskalierter Polymerreplikate der Rosenblütenblattstruktur wird anhand von drei verschiedenen, transparenten Folienmaterialien diskutiert. Sowohl für Polymethylmethacrylat (PMMA), Polycarbonat (PC), und Fluorethylen-Propylen (FEP) wird mit Hilfe des entwickelten Replikationsverfahrens eine hervorragende Strukturtreue über mehrere Längenskalen hinweg, vom sub-Mikrometer Bereich bis hin zu makroskopischen Merkmalen, mit gleichzeitig nahezu durchgängiger Strukturierung bei einer gesamten Strukturfläche von bis zu 12.5 cm×10.0 cm pro Replikat erzielt. Als vorderseitige Beschichtung für Kupfer-Indium-Gallium-Diselenid (CIGS) Solarzellen erweisen sich heißgeprägten Rosenreplikate als effektive Antireflex- und Light-Trapping-Maßnahme für einen breiten Spektralbereich und besonders für Lichteinfallswinkel >50°. Mit heißgeprägten Rosenreplikaten aus PMMA lässt sich sogar bei senkrechtem Lichteinfall eine gegenüber einer optimierten Magnesiumfluorid (MgF2) Antireflexbeschichtung verbesserte Antireflexwirkung feststellen. Optoelektronische Messungen bestätigen, dass sich diese Reflexionsverminderung auch entsprechend auf die Nennleistung der Solarzellen auswirkt, mit einer um im Mittel um 5.7%±0.6% gesteigerten Umwandlungseffizienz (verglichen mit den jeweiligen Solarzellen vor Aufbringung der Antireflexschichten) im Falle von PMMA Rosenreplikaten und 4.5%±1.6% für MgF2 Dünnschicht-Antireflexbeschichtungen. Weiter wird gezeigt, dass heißgeprägte Rosenreplikate auch mit wasserabweisenden Eigenschaften (mit einem statischer Kontaktwinkel von 134.4°±4.3°) erzeugt werden können, sogar ohne dabei auf zusätzliche Schritte zur Oberflächenmodifikation zurückgreifen zu müssen. Dazu wird als Ausgangsmaterial für den Heißprägeprozess ein Polymermaterial mit geringer freier Oberflächenenergie benötigt, was beispielsweise bei FEP gegeben ist. Wassertropfen, die auf geneigte FEP Rosenreplikate fallen, perlen von diesen sofort und restlos ab, was auf eine potentielle Eignung von FEP Rosenreplikaten zur Produktion selbstreinigender Solarmodule hindeutet. Der Leistungszuwachs, der durch die Anwendung der hochskalierten PMMA Rosenreplikate bewirkt wird, wird des Weiteren auch unter realistischen Betriebsbedingungen über neun Monaten Betrieb unter Außenbedingungen in Karlsruhe (Deutschland) untersucht, und zwar für 10 cm×10 cm CIGS und siliziumbasierte Solarmodule unter verschiedenen Modulneigungswinkeln und Modulorientierungen. Besonders hohe Steigerungen der täglichen Energieausbeute verglichen mit einem Referenzmodul ohne strukturierte Polymerfolie von bis zu deutlich über 10% werden dabei vor allem unter Aufstellbedingungen gemessen, die mit viel direkter Sonneneinstrahlung unter schrägem Lichteinfall einhergehen. Mit Hilfe beschleunigter Alterungs- und Abnutzungstests, welche standardisierten Testprotokollen aus der PV Industrie nachempfunden sind, wird außerdem auf die potentielle Langzeiteignung solch strukturierter Folien auf Solarmoduloberflächen hingewiesen. Außerdem werden die optischen Eigenschaften typischer Blütenblattstrukturen auf Solarzellen mit Hilfe einer speziell entwickelten 3D Mikrostruktur-Modellierungs- und Simulationsroutine, basierend auf Monte-Carlo-Raytracing und der Transfer-Matrix-Methode, hinsichtlich des Einflusses ungeordneter Strukturbausteine auf die Lichteinkopplungseigenschaften im Detail diskutiert. Durch Variation der Stärke der strukturellen Unordnung sowohl in der Höhe, der Anordnung, als auch der Neigung der Strukturbausteine der betrachteten, Blütenblattepidermis-inspirierten Mikrostrukturen lässt sich zeigen, dass ihre winkelabhängigen Reflexionseigenschaften nur schwach von Unordnung abhängen und in erster Linie vom mittleren Aspektverhältnis und der mittleren Packungsdichte der Strukturbausteine bestimmt werden. Schließlich werden die Polarisationseigenschaften von an Solarmodulen reflektiertem Licht hinsichtlich der möglichen schädlichen Auswirkungen auf polarotaktische Insektenarten diskutiert. Die vorderseitige Glasabdeckung herkömmlicher Solarmodule reflektiert aufgrund ihrer glatten Oberfläche linear polarisiertes Licht, wobei der Polarisationsgrad vom Einfallswinkel/ Betrachtungswinkel abhängt (vollständige lineare Polarisation bei Betrachtung unter dem Brewster-Winkel). Unbeabsichtigt wird dadurch der Insektenfauna geschadet, da polarotaktische Insekten Solarmodule als solche nicht erkennen und diese fälschlicherweise oft als Gewässer identifizieren, was dann beispielsweise eine Eierablage an einem ungeeigneten Ort und damit den Verlust der Nachkommen zur Folge haben kann. Experimente im Freifeld zeigen jedoch erstmals, dass keinerlei derartige schädliche Anziehungswirkung auf polarotaktische Eintagsfliegen (Ephemeroptera: Ephemera danica) und Bremsen (Diptera: Tabanidae) im Falle von PMMA Rosenreplikaten auf Solarmodulen zu befürchten ist. Basierend auf bildgebender Polarimetrie und Monte-Carlo-Raytracing-Simulationen werden diese Resultate auf die optischen Eigenschaften mikrostrukturierter Oberflächen zurückgeführt

Research and technology, 1992

Selected research and technology activities at Ames Research Center, including the Moffett Field site and the Dryden Flight Research Facility, are summarized. These activities exemplify the Center's varied and productive research efforts for 1992

Biotechnology

Biotechnological problems of man machine systems required for long duration space flight