Subpixel-Filterung für eine autostereoskopische Multiperspektiven-3-D-Darstellung hoher Qualität

Die stereoskopische 3-D-Darstellung beruht auf der naturgetreuen Präsentation verschiedener Perspektiven für das rechte und linke Auge. Sie erlangt in der Medizin, der Architektur, im Design sowie bei Computerspielen und im Kino, zukünftig möglicherweise auch im Fernsehen, eine immer größere Bedeutung. 3-D-Displays dienen der zusätzlichen Wiedergabe der räumlichen Tiefe und lassen sich grob in die vier Gruppen Stereoskope und Head-mounted-Displays, Brillensysteme, autostereoskopische Displays sowie echte 3-D-Displays einteilen. Darunter besitzt der autostereoskopische Ansatz ohne Brillen, bei dem N≥2 Perspektiven genutzt werden, ein hohes Potenzial. Die beste Qualität in dieser Gruppe kann mit der Methode der Integral Photography, die sowohl horizontale als auch vertikale Parallaxe kodiert, erreicht werden. Allerdings ist das Verfahren sehr aufwendig und wird deshalb wenig genutzt. Den besten Kompromiss zwischen Leistung und Preis bieten präzise gefertigte Linsenrasterscheiben (LRS), die hinsichtlich Lichtausbeute und optischen Eigenschaften den bereits früher bekannten Barrieremasken überlegen sind. Insbesondere für die ergonomisch günstige Multiperspektiven-3-D-Darstellung wird eine hohe physikalische Monitorauflösung benötigt. Diese ist bei modernen TFT-Displays schon recht hoch. Eine weitere Verbesserung mit dem theoretischen Faktor drei erreicht man durch gezielte Ansteuerung der einzelnen, nebeneinander angeordneten Subpixel in den Farben Rot, Grün und Blau. Ermöglicht wird dies durch die um etwa eine Größenordnung geringere Farbauflösung des menschlichen visuellen Systems im Vergleich zur Helligkeitsauflösung. Somit gelingt die Implementierung einer Subpixel-Filterung, welche entsprechend den physiologischen Gegebenheiten mit dem in Luminanz und Chrominanz trennenden YUV-Farbmodell arbeitet. Weiterhin erweist sich eine Schrägstellung der Linsen im Verhältnis von 1:6 als günstig. Farbstörungen werden minimiert, und die Schärfe der Bilder wird durch eine weniger systematische Vergrößerung der technologisch unvermeidbaren Trennelemente zwischen den Subpixeln erhöht. Der Grad der Schrägstellung ist frei wählbar. In diesem Sinne ist die Filterung als adaptiv an den Neigungswinkel zu verstehen, obwohl dieser Wert für einen konkreten 3-D-Monitor eine Invariante darstellt. Die zu maximierende Zielgröße ist der Parameter Perspektiven-Pixel als Produkt aus Anzahl der Perspektiven N und der effektiven Auflösung pro Perspektive. Der Idealfall einer Verdreifachung wird praktisch nicht erreicht. Messungen mit Hilfe von Testbildern sowie Schrifterkennungstests lieferten einen Wert von knapp über 2. Dies ist trotzdem als eine signifikante Verbesserung der Qualität der 3-D-Darstellung anzusehen. In der Zukunft sind weitere Verbesserungen hinsichtlich der Zielgröße durch Nutzung neuer, feiner als TFT auflösender Technologien wie LCoS oder OLED zu erwarten. Eine Kombination mit der vorgeschlagenen Filtermethode wird natürlich weiterhin möglich und ggf. auch sinnvoll sein.

Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.

On Vessiot's Theory of Partial Differential Equations

The object of research presented here is Vessiot's theory of partial differential equations: for a given differential equation one constructs a distribution both tangential to the differential equation and contained within the contact distribution of the jet bundle. Then within it, one seeks n-dimensional subdistributions which are transversal to the base manifold, the integral distributions. These consist of integral elements, and these again shall be adapted so that they make a subdistribution which closes under the Lie-bracket. This then is called a flat Vessiot connection. Solutions to the differential equation may be regarded as integral manifolds of these distributions. In the first part of the thesis, I give a survey of the present state of the formal theory of partial differential equations: one regards differential equations as fibred submanifolds in a suitable jet bundle and considers formal integrability and the stronger notion of involutivity of differential equations for analyzing their solvability. An arbitrary system may (locally) be represented in reduced Cartan normal form. This leads to a natural description of its geometric symbol. The Vessiot distribution now can be split into the direct sum of the symbol and a horizontal complement (which is not unique). The n-dimensional subdistributions which close under the Lie bracket and are transversal to the base manifold are the sought tangential approximations for the solutions of the differential equation. It is now possible to show their existence by analyzing the structure equations. Vessiot's theory is now based on a rigorous foundation. Furthermore, the relation between Vessiot's approach and the crucial notions of the formal theory (like formal integrability and involutivity of differential equations) is clarified. The possible obstructions to involution of a differential equation are deduced explicitly. In the second part of the thesis it is shown that Vessiot's approach for the construction of the wanted distributions step by step succeeds if, and only if, the given system is involutive. Firstly, an existence theorem for integral distributions is proven. Then an existence theorem for flat Vessiot connections is shown. The differential-geometric structure of the basic systems is analyzed and simplified, as compared to those of other approaches, in particular the structure equations which are considered for the proofs of the existence theorems: here, they are a set of linear equations and an involutive system of differential equations. The definition of integral elements given here links Vessiot theory and the dual Cartan-Kähler theory of exterior systems. The analysis of the structure equations not only yields theoretical insight but also produces an algorithm which can be used to derive the coefficients of the vector fields, which span the integral distributions, explicitly. Therefore implementing the algorithm in the computer algebra system MuPAD now is possible.

Water Resource Pollution and Impacts on the local livelihood: A case study of Beas River in Kullu District, India

The rivers are considered as the life line of any country since they make water available for our domestic, industrial and recreational functions. The quality of river water signifies the health status and hygienic aspects of a particular region, but the quality of these life lines is continuously deteriorating due to discharge of sewage, garbage and industrial effluents into them. Thrust on water demand has increased manifolds due to the increased population, therefore tangible efforts to make the water sources free from pollution is catching attention all across the globe. This paper attempts to highlight the trends in water quality change of River Beas, right from Manali to Larji in India. This is an important river in the state of Himachal Pradesh and caters to the need of water for Manali and Kullu townships, besides other surrounding rural areas. The Manali-Larji Beas river stretch is exposed to the flow of sewage, garbage and muck resulting from various project activities, thereby making it vulnerable to pollution. In addition, the influx of thousands of tourists to these towns also contributes to the pollution load by their recreational and other tourist related activities. Pollution of this river has ultimately affected the livelihood of local population in this region. Hence, water quality monitoring was carried out for the said stretch between January, 2010 and January, 2012 at 15 various locations on quarterly basis, right from the upstream of Manali town and up to downstream of Larji dam. Temperature, color, odor, D.O. , pH, BOD, TSS, TC and FC has been the parameters that were studied. This study gives the broad idea about the characteristics of water at locations in the said river stretch, and suggestions for improving water quality and livelihood of local population in this particular domain.

Controlling the transport of an ion: classical and quantum mechanical solutions

The accurate transport of an ion over macroscopic distances represents a challenging control problem due to the different length and time scales that enter and the experimental limitations on the controls that need to be accounted for. Here, we investigate the performance of different control techniques for ion transport in state-of-the-art segmented miniaturized ion traps. We employ numerical optimization of classical trajectories and quantum wavepacket propagation as well as analytical solutions derived from invariant based inverse engineering and geometric optimal control. The applicability of each of the control methods depends on the length and time scales of the transport. Our comprehensive set of tools allows us make a number of observations. We find that accurate shuttling can be performed with operation times below the trap oscillation period. The maximum speed is limited by the maximum acceleration that can be exerted on the ion. When using controls obtained from classical dynamics for wavepacket propagation, wavepacket squeezing is the only quantum effect that comes into play for a large range of trapping parameters. We show that this can be corrected by a compensating force derived from invariant based inverse engineering, without a significant increase in the operation time.