Non Uniform Multiresolution Method for Optical Flow and Phase Portrait Models: Environmental Applications

Projet AIRIn this paper we define a complete framework for processing large image sequences for a global monitoring of short range oceanographic and atmospheric processes. This framework is based on the use of a non quadratic regularization technique in optical flow computation that preserves flow discontinuities. We also show that using an appropriate tessellation of the image according to an estimate of the motion field can improve optical flow accuracy and yields more reliable flows. This method defines a non uniform multiresolution approach for coarse to fine grid generation. It allows to locally increase the resolution of the grid according to the studied problem. Each added node refines the grid in a region of interest and increases the numerical accuracy of the solution in this region. We make use of such a method for solving the optical flow equation with a non quadratic regularization scheme allowing the computation of optical flow field while preserving its discontinuities. The second part of the paper deals with the interpretation of the obtained displacement field. We make use of a phase portrait model with a new formulation of the approximation of an oriented flow field allowing to consider arbitrary polynomial phase portrait models for characterizing salient flow features. This new framework is used for processing oceanographic and atmospheric image sequences and presents an alternative to complex physical modeling techniques

Validation of surface velocity estimated from satellite images

This report concerns the validation of surface velocity estimated from satellite images. The estimation is obtained with a dynamic model based on shallow-water equations. We first compare the stationary assumption to the shallow-water heuristics to justify our choice. Second, we quantify the quality of the estimation by measuring the misfit between the model output and the altimetry measures. Experiments are achieved on Sea Surface Temperature data acquired by the NOAA/AVHRR satellites over the Black Sea. The altimetry measures are obtained by two radar sensors: Envisat and GFO. The good adequacy between the shallow-water output and the altimetry data validates our motion estimation approach.Ce rapport de recherche concerne la validation de l'estimation de la vitesse de surface à partir d'images satellite. Cette estimation est effectuée avec un modèle de la dynamique, basé sur les équations shallow-water. Nous comparons d'abord l'hypothèse de stationnarité aux équations shallow-water afin de justifier notre choix. Puis, nous quantifions la qualité des estimations en mesurant l'écart entre la sortie du modèle et les mesures d'altimétrie. Les expérimentations sont effectuées en utilisant des données de température de surface, acquises au-dessus de la Mer Noire avec les satellites NOAA/AVHRR. Les mesures altimétriques proviennent de deux capteurs radar : Envisat et GFO. La bonne adéquation entre la sortie du modèle shallow-water et les données altimétriques valide notre approche d'estimation du mouvement

Validation of surface velocity estimated from satellite images

This report concerns the validation of surface velocity estimated from satellite images. The estimation is obtained with a dynamic model based on shallow-water equations. We first compare the stationary assumption to the shallow-water heuristics to justify our choice. Second, we quantify the quality of the estimation by measuring the misfit between the model output and the altimetry measures. Experiments are achieved on Sea Surface Temperature data acquired by the NOAA/AVHRR satellites over the Black Sea. The altimetry measures are obtained by two radar sensors: Envisat and GFO. The good adequacy between the shallow-water output and the altimetry data validates our motion estimation approach.Ce rapport de recherche concerne la validation de l'estimation de la vitesse de surface à partir d'images satellite. Cette estimation est effectuée avec un modèle de la dynamique, basé sur les équations shallow-water. Nous comparons d'abord l'hypothèse de stationnarité aux équations shallow-water afin de justifier notre choix. Puis, nous quantifions la qualité des estimations en mesurant l'écart entre la sortie du modèle et les mesures d'altimétrie. Les expérimentations sont effectuées en utilisant des données de température de surface, acquises au-dessus de la Mer Noire avec les satellites NOAA/AVHRR. Les mesures altimétriques proviennent de deux capteurs radar : Envisat et GFO. La bonne adéquation entre la sortie du modèle shallow-water et les données altimétriques valide notre approche d'estimation du mouvement

Advanced photonic and electronic systems - WILGA 2017

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers more than 350 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET by PAN and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2017 was the XL edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2017 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 159

This bibliography lists 257 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1976

The Growth and Morphology of Small Ice Crystals in a Diffusion Chamber

Small water ice crystals are the main component of cold tropospheric clouds such as cirrus. Because these clouds cover large areas of our planet, their role in the radiation budget of incoming and outgoing radiation to the planet’s surface is important. At present, the representation of these clouds in climate and weather models is subject to improvements: a large part of the uncertainty error stems from the lack of precise micro-physical and radiation model schemes for ice crystal clouds. To improve the cloud representations, a better understanding of the life time dynamics of the clouds and their composition is necessary, comprising a detailed understanding of the ice particle genesis, and development over their lifetime. It is especially important to understand how the development of ice crystals over time is linked to the changes in observable variables such as water vapour content and temperature and how they change the light scattering properties of the crystals. Recent remote and aircraft based in-situ measurements have shown that many ice particles show a light scattering behaviour typical for crystals having rough surfaces or being of complex geometrical shapes. The aim of this thesis was to develop the experimental setup and experiments to investigate this further by studying the surface morphology of small water ice crystals using scanning electron microscopy (SEM). The experiments I developed study the growth of water ice crystals inside an SEM chamber under controlled environmental conditions. The influence of water vapour supersaturation, pressure and temperature is investigated. I demonstrate how to retrieve the surface topology from observed crystals for use as input to computational light scattering codes to derive light scattering phase functions and asymmetry parameters, which can be used as input into atmospheric models. Difficulties with the method for studying the growth of water ice crystals, such as the effect of the electron beam-gas ionization and charging effects, the problem of facilitating repeated and localized ice growth, and the effect of radiative influences on the crystal growth are discussed. A broad set of nucleation target materials is studied. In a conclusion, I demonstrate that the method is suitable to study the surface morphologies, but is experimentally very challenging and many precautions must be taken, such as imaging only once and preventing radiative heat exchange between the chamber walls and the crystals to avoid unwanted effects on the crystal morphology. It is also left as a question if a laboratory experiment, where crystals will need to be grown in connection to a substrate, can represent the real world well enough. Deriving the required light scattering data in-situ might be an alternative, easier way to collect data for modelling use

Advances in Spacecraft Systems and Orbit Determination

"Advances in Spacecraft Systems and Orbit Determinations", discusses the development of new technologies and the limitations of the present technology, used for interplanetary missions. Various experts have contributed to develop the bridge between present limitations and technology growth to overcome the limitations. Key features of this book inform us about the orbit determination techniques based on a smooth research based on astrophysics. The book also provides a detailed overview on Spacecraft Systems including reliability of low-cost AOCS, sliding mode controlling and a new view on attitude controller design based on sliding mode, with thrusters. It also provides a technological roadmap for HVAC optimization. The book also gives an excellent overview of resolving the difficulties for interplanetary missions with the comparison of present technologies and new advancements. Overall, this will be very much interesting book to explore the roadmap of technological growth in spacecraft systems

Robust Modular Feature-Based Terrain-Aided Visual Navigation and Mapping

The visual feature-based Terrain-Aided Navigation (TAN) system presented in this thesis addresses the problem of constraining inertial drift introduced into the location estimate of Unmanned Aerial Vehicles (UAVs) in GPS-denied environment. The presented TAN system utilises salient visual features representing semantic or human-interpretable objects (roads, forest and water boundaries) from onboard aerial imagery and associates them to a database of reference features created a-priori, through application of the same feature detection algorithms to satellite imagery. Correlation of the detected features with the reference features via a series of the robust data association steps allows a localisation solution to be achieved with a finite absolute bound precision defined by the certainty of the reference dataset. The feature-based Visual Navigation System (VNS) presented in this thesis was originally developed for a navigation application using simulated multi-year satellite image datasets. The extension of the system application into the mapping domain, in turn, has been based on the real (not simulated) flight data and imagery. In the mapping study the full potential of the system, being a versatile tool for enhancing the accuracy of the information derived from the aerial imagery has been demonstrated. Not only have the visual features, such as road networks, shorelines and water bodies, been used to obtain a position ’fix’, they have also been used in reverse for accurate mapping of vehicles detected on the roads into an inertial space with improved precision. Combined correction of the geo-coding errors and improved aircraft localisation formed a robust solution to the defense mapping application. A system of the proposed design will provide a complete independent navigation solution to an autonomous UAV and additionally give it object tracking capability

On the use of smartphones as novel photogrammetric water gauging instruments: Developing tools for crowdsourcing water levels

The term global climate change is omnipresent since the beginning of the last decade. Changes in the global climate are associated with an increase in heavy rainfalls that can cause nearly unpredictable flash floods. Consequently, spatio-temporally high-resolution monitoring of rivers becomes increasingly important. Water gauging stations continuously and precisely measure water levels. However, they are rather expensive in purchase and maintenance and are preferably installed at water bodies relevant for water management. Small-scale catchments remain often ungauged. In order to increase the data density of hydrometric monitoring networks and thus to improve the prediction quality of flood events, new, flexible and cost-effective water level measurement technologies are required. They should be oriented towards the accuracy requirements of conventional measurement systems and facilitate the observation of water levels at virtually any time, even at the smallest rivers. A possible solution is the development of a photogrammetric smartphone application (app) for crowdsourcing water levels, which merely requires voluntary users to take pictures of a river section to determine the water level. Today’s smartphones integrate high-resolution cameras, a variety of sensors, powerful processors, and mass storage. However, they are designed for the mass market and use low-cost hardware that cannot comply with the quality of geodetic measurement technology. In order to investigate the potential for mobile measurement applications, research was conducted on the smartphone as a photogrammetric measurement instrument as part of the doctoral project. The studies deal with the geometric stability of smartphone cameras regarding device-internal temperature changes and with the accuracy potential of rotation parameters measured with smartphone sensors. The results show a high, temperature-related variability of the interior orientation parameters, which is why the calibration of the camera should be carried out during the immediate measurement. The results of the sensor investigations show considerable inaccuracies when measuring rotation parameters, especially the compass angle (errors up to 90° were observed). The same applies to position parameters measured by global navigation satellite system (GNSS) receivers built into smartphones. According to the literature, positional accuracies of about 5 m are possible in best conditions. Otherwise, errors of several 10 m are to be expected. As a result, direct georeferencing of image measurements using current smartphone technology should be discouraged. In consideration of the results, the water gauging app Open Water Levels (OWL) was developed, whose methodological development and implementation constituted the core of the thesis project. OWL enables the flexible measurement of water levels via crowdsourcing without requiring additional equipment or being limited to specific river sections. Data acquisition and processing take place directly in the field, so that the water level information is immediately available. In practice, the user captures a short time-lapse sequence of a river bank with OWL, which is used to calculate a spatio-temporal texture that enables the detection of the water line. In order to translate the image measurement into 3D object space, a synthetic, photo-realistic image of the situation is created from existing 3D data of the river section to be investigated. Necessary approximations of the image orientation parameters are measured by smartphone sensors and GNSS. The assignment of camera image and synthetic image allows for the determination of the interior and exterior orientation parameters by means of space resection and finally the transfer of the image-measured 2D water line into the 3D object space to derive the prevalent water level in the reference system of the 3D data. In comparison with conventionally measured water levels, OWL reveals an accuracy potential of 2 cm on average, provided that synthetic image and camera image exhibit consistent image contents and that the water line can be reliably detected. In the present dissertation, related geometric and radiometric problems are comprehensively discussed. Furthermore, possible solutions, based on advancing developments in smartphone technology and image processing as well as the increasing availability of 3D reference data, are presented in the synthesis of the work. The app Open Water Levels, which is currently available as a beta version and has been tested on selected devices, provides a basis, which, with continuous further development, aims to achieve a final release for crowdsourcing water levels towards the establishment of new and the expansion of existing monitoring networks.Der Begriff des globalen Klimawandels ist seit Beginn des letzten Jahrzehnts allgegenwärtig. Die Veränderung des Weltklimas ist mit einer Zunahme von Starkregenereignissen verbunden, die nahezu unvorhersehbare Sturzfluten verursachen können. Folglich gewinnt die raumzeitlich hochaufgelöste Überwachung von Fließgewässern zunehmend an Bedeutung. Pegelmessstationen erfassen kontinuierlich und präzise Wasserstände, sind jedoch in Anschaffung und Wartung sehr teuer und werden vorzugsweise an wasserwirtschaftlich-relevanten Gewässern installiert. Kleinere Gewässer bleiben häufig unbeobachtet. Um die Datendichte hydrometrischer Messnetze zu erhöhen und somit die Vorhersagequalität von Hochwasserereignissen zu verbessern, sind neue, kostengünstige und flexibel einsetzbare Wasserstandsmesstechnologien erforderlich. Diese sollten sich an den Genauigkeitsanforderungen konventioneller Messsysteme orientieren und die Beobachtung von Wasserständen zu praktisch jedem Zeitpunkt, selbst an den kleinsten Flüssen, ermöglichen. Ein Lösungsvorschlag ist die Entwicklung einer photogrammetrischen Smartphone-Anwendung (App) zum Crowdsourcing von Wasserständen mit welcher freiwillige Nutzer lediglich Bilder eines Flussabschnitts aufnehmen müssen, um daraus den Wasserstand zu bestimmen. Heutige Smartphones integrieren hochauflösende Kameras, eine Vielzahl von Sensoren, leistungsfähige Prozessoren und Massenspeicher. Sie sind jedoch für den Massenmarkt konzipiert und verwenden kostengünstige Hardware, die nicht der Qualität geodätischer Messtechnik entsprechen kann. Um das Einsatzpotential in mobilen Messanwendungen zu eruieren, sind Untersuchungen zum Smartphone als photogrammetrisches Messinstrument im Rahmen des Promotionsprojekts durchgeführt worden. Die Studien befassen sich mit der geometrischen Stabilität von Smartphone-Kameras bezüglich geräteinterner Temperaturänderungen und mit dem Genauigkeitspotential von mit Smartphone-Sensoren gemessenen Rotationsparametern. Die Ergebnisse zeigen eine starke, temperaturbedingte Variabilität der inneren Orientierungsparameter, weshalb die Kalibrierung der Kamera zum unmittelbaren Messzeitpunkt erfolgen sollte. Die Ergebnisse der Sensoruntersuchungen zeigen große Ungenauigkeiten bei der Messung der Rotationsparameter, insbesondere des Kompasswinkels (Fehler von bis zu 90° festgestellt). Selbiges gilt auch für Positionsparameter, gemessen durch in Smartphones eingebaute Empfänger für Signale globaler Navigationssatellitensysteme (GNSS). Wie aus der Literatur zu entnehmen ist, lassen sich unter besten Bedingungen Lagegenauigkeiten von etwa 5 m erreichen. Abseits davon sind Fehler von mehreren 10 m zu erwarten. Infolgedessen ist von einer direkten Georeferenzierung von Bildmessungen mittels aktueller Smartphone-Technologie abzusehen. Unter Berücksichtigung der gewonnenen Erkenntnisse wurde die Pegel-App Open Water Levels (OWL) entwickelt, deren methodische Entwicklung und Implementierung den Kern der Arbeit bildete. OWL ermöglicht die flexible Messung von Wasserständen via Crowdsourcing, ohne dabei zusätzliche Ausrüstung zu verlangen oder auf spezifische Flussabschnitte beschränkt zu sein. Datenaufnahme und Verarbeitung erfolgen direkt im Feld, so dass die Pegelinformationen sofort verfügbar sind. Praktisch nimmt der Anwender mit OWL eine kurze Zeitraffersequenz eines Flussufers auf, die zur Berechnung einer Raum-Zeit-Textur dient und die Erkennung der Wasserlinie ermöglicht. Zur Übersetzung der Bildmessung in den 3D-Objektraum wird aus vorhandenen 3D-Daten des zu untersuchenden Flussabschnittes ein synthetisches, photorealistisches Abbild der Aufnahmesituation erstellt. Erforderliche Näherungen der Bildorientierungsparameter werden von Smartphone-Sensoren und GNSS gemessen. Die Zuordnung von Kamerabild und synthetischem Bild erlaubt die Bestimmung der inneren und äußeren Orientierungsparameter mittels räumlichen Rückwärtsschnitt. Nach Rekonstruktion der Aufnahmesituation lässt sich die im Bild gemessene 2D-Wasserlinie in den 3D-Objektraum projizieren und der vorherrschende Wasserstand im Referenzsystem der 3D-Daten ableiten. Im Soll-Ist-Vergleich mit konventionell gemessenen Pegeldaten zeigt OWL ein erreichbares Genauigkeitspotential von durchschnittlich 2 cm, insofern synthetisches und reales Kamerabild einen möglichst konsistenten Bildinhalt aufweisen und die Wasserlinie zuverlässig detektiert werden kann. In der vorliegenden Dissertation werden damit verbundene geometrische und radiometrische Probleme ausführlich diskutiert sowie Lösungsansätze, auf der Basis fortschreitender Entwicklungen von Smartphone-Technologie und Bildverarbeitung sowie der zunehmenden Verfügbarkeit von 3D-Referenzdaten, in der Synthese der Arbeit vorgestellt. Mit der gegenwärtig als Betaversion vorliegenden und auf ausgewählten Geräten getesteten App Open Water Levels wurde eine Basis geschaffen, die mit kontinuierlicher Weiterentwicklung eine finale Freigabe für das Crowdsourcing von Wasserständen und damit den Aufbau neuer und die Erweiterung bestehender Monitoring-Netzwerke anstrebt