This thesis presents a very efficient hybrid method for analysis and design of optical and passive photonic devices. The main focus is on unbounded wave structures. This class of photonic systems are in general very large in terms of the wavelength of the driving optical sources. The size of the problem space makes the electromagnetic modelling of these structure a very challenging problem. Our approach and main contribution has been to combine or hybridize three methods that together can handle this class of photonic structures as a whole. <br /><br /> The basis of the hybrid method is a novel Gaussian Beam Tracing method GBT. Gaussian Beams (GB) are very suitable elementary functions for tracing and tracking purposes due to their finite extent and the fact that they are good approximations for actual laser beams. The GBT presented in this thesis is based on the principle of phase matching. This method can be used to model the reflection and refraction of Gaussian beams from general curved surfaces as long as the curvature of the surface is relatively small. It can also model wave propagation in free space. The developed GBT is extremely fast as it essentially uses simple algebraic equations to find the parameters of the reflected and refracted beams once the parameters of the incident beam is known. Therefore sections of the systems whose dimensions are large relative to the optical wavelength are simulated by the GBT method. <br /><br /> Fields entering a photonic system may not possess an exact Gaussian profile. For example if an aperture limits the input laser to the system, the field is no longer a GB. In these and other similar cases the field at some aperture plane needs to be expanded into a sum of GBs. Gabor expansion has been used for this purpose. This method allows any form of field distribution on a flat or curved surface to be expanded into a sum of GBs. The resultant GBs are then launched inside the system and tracked by GBT. Calculation of the coefficients of the Gabor series is very fast (1-2 minutes on a typical computer for most applications). <br /><br /> In some cases the dimensions or physical properties of structures do not allow the application of the GBT method. For example if the curvature of a surface is very large (or its radius of curvature is very small) or if the surface contains sharp edges or sub-wavelength dimensions GBT is no longer valid. In these cases we have utilized the Finite Difference Time Domain method (FDTD). FDTD is a rigorous and very accurate full wave electromagnetic solver. The time domain form of Maxwell's equations are discretized and solved. No matrix inversion is needed for this method. If the size of the structure that needs to be analyzed is large relative to the wavelength FDTD can become increasingly time consuming. Nevertheless once a structure is simulated using FDTD for a given input, the output is expanded using Gabor expansion and the resultant beams can then be efficiently propagated through any desired system using GBT. For example if a diffraction grating is illuminated by some source, once the reflection is found using FDTD, it can be propagated very efficiently through any kind of lens or prism (or other optical structures) using GBT. Therefore the overall computational efficiency of the hybrid method is very high compared to other methods.

This thesis presents a new technique to identify a 2D mask showing the extent of particulate aerosol distributions in satellite imagery. This technique uses a supervised texture classication approach, and utilises data from two distinct satellite sources. The vertical feature mask (VFM) product from the CALIPSO lidar, provides an accurate description of the aerosol content of the atmosphere but has a limited footprint and coverage. The CALIPSO VFM is used to provide training data in order to for classiers to be applied to other imagery, namely data from the spinning enhanced visible and infrared imager (SEVIRI) on the MSG satellite. The output from the classication is a 2D mask representing the locations of the particulate aerosol of interest within the SEVIRI image. This approach has been demonstrated on test cases over land and ocean, and shows a good agreement with other techniques for the detection of particulate aerosol. However, the supervised texture approach provides outputs at a higher resolution than the existing methods and the same approach is applicable over land and ocean and therefore shows the advantages compared to the current techniques. Furthermore, the coverage of the approach can be further extended using signature extension and chain classication. Signature extension was applied to one of the test cases to monitor the same geographical region with temporal extension away from the initial supervised classication. The experiments showed that it was possible to extend the coverage for ±90 minutes from the original classication and indicates the possibility of greater extension over larger temporal windows.

The problem of characterization of active sonar target response has important applications in many fields, including the currently cost-prohibitive recovery of unexploded ordinance on the ocean floor. We present a method for recognizing these objects using a multidisciplinary approach that fuses machine learning, signal processing, and feature engineering. In short, by taking inspiration from other fields, we solve the problem of object recognition in shallow water in an inexpensive way. These techniques add to the body of explored knowledge in the field of active sonar processing and address real-world problems in the process.

Thesis (Ph.D.)--University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (March 1, 2007) Vita. Includes bibliographical references.

This thesis presents a very efficient hybrid method for analysis and design of optical and passive photonic devices. The main focus is on unbounded wave structures. This class of photonic systems are in general very large in terms of the wavelength of the driving optical sources. The size of the problem space makes the electromagnetic modelling of these structure a very challenging problem. Our approach and main contribution has been to combine or hybridize three methods that together can handle this class of photonic structures as a whole. <br /><br /> The basis of the hybrid method is a novel Gaussian Beam Tracing method GBT. Gaussian Beams (GB) are very suitable elementary functions for tracing and tracking purposes due to their finite extent and the fact that they are good approximations for actual laser beams. The GBT presented in this thesis is based on the principle of phase matching. This method can be used to model the reflection and refraction of Gaussian beams from general curved surfaces as long as the curvature of the surface is relatively small. It can also model wave propagation in free space. The developed GBT is extremely fast as it essentially uses simple algebraic equations to find the parameters of the reflected and refracted beams once the parameters of the incident beam is known. Therefore sections of the systems whose dimensions are large relative to the optical wavelength are simulated by the GBT method. <br /><br /> Fields entering a photonic system may not possess an exact Gaussian profile. For example if an aperture limits the input laser to the system, the field is no longer a GB. In these and other similar cases the field at some aperture plane needs to be expanded into a sum of GBs. Gabor expansion has been used for this purpose. This method allows any form of field distribution on a flat or curved surface to be expanded into a sum of GBs. The resultant GBs are then launched inside the system and tracked by GBT. Calculation of the coefficients of the Gabor series is very fast (1-2 minutes on a typical computer for most applications). <br /><br /> In some cases the dimensions or physical properties of structures do not allow the application of the GBT method. For example if the curvature of a surface is very large (or its radius of curvature is very small) or if the surface contains sharp edges or sub-wavelength dimensions GBT is no longer valid. In these cases we have utilized the Finite Difference Time Domain method (FDTD). FDTD is a rigorous and very accurate full wave electromagnetic solver. The time domain form of Maxwell's equations are discretized and solved. No matrix inversion is needed for this method. If the size of the structure that needs to be analyzed is large relative to the wavelength FDTD can become increasingly time consuming. Nevertheless once a structure is simulated using FDTD for a given input, the output is expanded using Gabor expansion and the resultant beams can then be efficiently propagated through any desired system using GBT. For example if a diffraction grating is illuminated by some source, once the reflection is found using FDTD, it can be propagated very efficiently through any kind of lens or prism (or other optical structures) using GBT. Therefore the overall computational efficiency of the hybrid method is very high compared to other methods.

With an increasing emphasis on personal privacy, security, and convenience, the security of identification system is an important issue nowadays. In this thesis, two intelligent identification systems, laser speckle image identification system and laser-based finger biometric system, are proposed to perform superior solutions for identification applications. In laser speckle image identification system, we investigated the characteristics of laser speckle as well as proposed an appropriate algorithm to establish this system. The proposed algorithm is a coarse-to-fine process which identifies laser speckle images systematically. In laser-based finger biometric system, a new biometric approach is described to proceed personal identification using a scanner with a low power laser scans across the surface of the finger and continuously recording the reflected intensity at a fixed position. Experimental results show that the recognition rates of the proposed system are both 100%.

L'objectif de ce travail de thèse est d'enrichir la formulation du Lancer de Faisceaux Gaussiens (LFG) et de tester sa capacité à répondre à certains des besoins actuels en calculs de propagation dans le domaine du Radar terrestre. Le LFG est envisagé comme une alternative possible aux méthodes classiques (Equation Parabolique, méthodes de rayons) en environnement complexe urbanisé, en particulier en présence d'obstacles latéraux, avec une cible située en non visibilité. La méthode de LFG "de base", qui utilise des expressions analytiques obtenues par approximation paraxiale, permet des calculs de propagation rapides en environnements complexes, sans problèmes de caustiques. Elle conduit à des résultats de précision satisfaisante dans le domaine millimétrique, par exemple pour des calculs de champs intra-bâtiments. Aux fréquences plus basses comme celles utilisées en Radar terrestre, elle est limitée par une prise en compte trop approximative des effets de diffraction et par l'élargissement spatial des faisceaux gaussiens au regard des dimensions des obstacles. La théorie des frames est utilisée dans cette thèse pour dépasser ces limites. La théorie des frames fournit un cadre rigoureux pour la décomposition initiale du champ rayonné en faisceaux gaussiens, et permet de calibrer le nombre et les directions des faisceaux à lancer. Dans ce travail de thèse, l'emploi de frames de fenêtres gaussiennes pour décomposer des distributions de champs ou de sources équivalentes est généralisé aux distributions de champs incidents sur des plans ou des portions de plans, choisis en fonction des obstacles rencontrés et des distances parcourues. Les champs rayonnés à partir de ces plans sont alors obtenus par sommation des faisceaux gaussiens lancés depuis ces frames dits de "re-décomposition". Les transformations de faisceaux gaussiens par des obstacles de taille limitée sont ainsi traitées par redécomposition : les faisceaux incidents partiellement interceptés par des surfaces limitées sont "re-décomposés" successivement sur deux frames de re-décomposition, à fenêtres "étroites" puis "larges", définis dans les plans de ces surfaces. Le frame à fenêtres "étroites" permet de traiter les discontinuités physiques, tandis que le frame à fenêtres "larges" permet de propager les champs transformés sous la forme de faisceaux "collimatés". Dans cette thèse, nous présentons une formulation de ces re-décompositions permettant une mise en œuvre numériquement efficace, grâce à des expressions analytiques approchées des coefficients de frame pour la première décomposition, et des éléments de la matrice de changement de frame pour la seconde. Cette formulation est mise en œuvre numériquement, et l'influence de différents paramètres sur la précision des re-décompositions est analysée. Finalement, l'algorithme de LFG enrichi de ces re-décompositions successives est utilisé dans un scénario simplifié proche de situations rencontrées en propagation Radar terrestre.

Recent studies have been done to create models that predict the response of the human visual system (HVS) based on how the HVS processes an image. The most widely known of these models is the Gabor model, since the Gabor patterns closely resemble the receptive filters in the human eye. The work of this thesis examines the use of Symlets to represent the HVS, since Symlets provide the benefit of orthogonality. One major problem with Symlets is that the energy is not stable in respective Symlet channels when the image patterns are translated spatially. This thesis addresses this problem by up sampling Symlets instead of down sampling, and thus creating shift invariant Symlets. This thesis then compares the representation of Gabor versus Symlet approach in predicting the response of the HVS to detecting print defect patterns such as banding and graining. In summary we noticed that Symlet prediction outperforms the Gabor prediction thus Symlets would be a good choice for HVS response prediction. We also concluded that for banding defect periodicity and size are important factors that affect the response of the HVS to the patterns. For graining defects we noticed that size does not greatly affect the response of the HVS to the defect patterns. We introduced our results using two set of performance metrics, the mean and median.

Thesis(M.S.)--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references.

Techn. Hochsch., Diss., 2003--Aachen.