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1
Blanke, William John. "Multiresolution techniques on a parallel multidisplay multiresolution image compositing system." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3035942.
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Camilleri, Kenneth P. "Multiresolution texture segmentation." Thesis, University of Surrey, 1999. http://epubs.surrey.ac.uk/843549/.
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The problem of unsupervised texture segmentation was studied and a texture segmentation algorithm was developed making use of the minimum number of prior assumptions. In particular, no prior information about the type of textures, the number of textures and the appropriate scale of analysis for each texture was required. The texture image was analysed by the multiresolution Gabor expansion. The Gabor expansion generates a large number of features for each image and the most suitable feature space for segmentation needs to be determined automatically. The two-point correlation function was used to test the separability of the distributions in each feature space. A measure was developed to evaluate evidence of multiple clusters from the two-point correlation function, making it possible to determine the most suitable feature space for clustering. Thus, at a given resolution level, the most appropriate feature space was selected and used to segment the image. Due to inherent ambiguities and limitations of the two-point correlation function, this feature space exploration and segmentation was performed several times at the same resolution level until no further evidence of multiple clusters was found, at which point, the process was repeated at the next finer resolution level. In this way, the image was progressively segmented, proceeding from coarse to fine Gabor resolution levels without any knowledge of the actual number of textures present. In order to refine the region-labelled image obtained at the end of the segmentation process, two postprocessing pixel-level algorithms were developed and implemented. The first was the mixed pixel classification algorithm which is based on the analysis of the effect of the averaging window at the boundary between two regions and re-assigns the pixel labels to improve the boundary localisation. Multiresolution probabilistic relaxation is the second postprocessing algorithm which we developed. This algorithm incorporates contextual evidence to relabel pixels close to the boundary in order to smooth it and improve its localisation. The results obtained were quantified by known error measures, as well as by new error measures which we developed. The quantified results were compared to similar results by other authors and show that our unsupervised algorithm performs as well as other methods which assume prior information.
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Bhalerao, Abhir. "Multiresolution image segmentation." Thesis, University of Warwick, 1991. http://wrap.warwick.ac.uk/60866/.
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Image segmentation is an important area in the general field of image processing and computer vision. It is a fundamental part of the 'low level' aspects of computer vision and has many practical applications such as in medical imaging, industrial automation and satellite imagery. Traditional methods for image segmentation have approached the problem either from localisation in class space using region information, or from localisation in position, using edge or boundary information. More recently, however, attempts have been made to combine both region and boundary information in order to overcome the inherent limitations of using either approach alone. In this thesis, a new approach to image segmentation is presented that integrates region and boundary information within a multiresolution framework. The role of uncertainty is described, which imposes a limit on the simultaneous localisation in both class and position space. It is shown how a multiresolution approach allows the trade-off between position and class resolution and ensures both robustness in noise and efficiency of computation. The segmentation is based on an image model derived from a general class of multiresolution signal models, which incorporates both region and boundary features. A four stage algorithm is described consisting of: generation of a low-pass pyramid, separate region and boundary estimation processes and an integration strategy. Both the region and boundary processes consist of scale-selection, creation of adjacency graphs, and iterative estimation within a general framework of maximum a posteriori (MAP) estimation and decision theory. Parameter estimation is performed in situ, and the decision processes are both flexible and spatially local, thus avoiding assumptions about global homogeneity or size and number of regions which characterise some of the earlier algorithms. A method for robust estimation of edge orientation and position is described which addresses the problem in the form of a multiresolution minimum mean square error (MMSE) estimation. The method effectively uses the spatial consistency of output of small kernel gradient operators from different scales to produce more reliable edge position and orientation and is effective at extracting boundary orientations from data with low signal-to-noise ratios. Segmentation results are presented for a number of synthetic and natural images which show the cooperative method to give accurate segmentations at low signal-to-noise ratios (0 dB) and to be more effective than previous methods at capturing complex region shapes.
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陳健華 and Kin-wah Chan. "Multiresolution polygonal approximation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B30257402.
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Chan, Kin-wah. "Multiresolution polygonal approximation /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1985965X.
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Salem, Mohammed Abdel-Megeed Mohammed. "Multiresolution image segmentation." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2008. http://dx.doi.org/10.18452/15846.
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Systeme der Computer Vision spielen in der Automatisierung vieler Prozesse eine wichtige Rolle. Die wichtigste Aufgabe solcher Systeme ist die Automatisierung des visuellen Erkennungsprozesses und die Extraktion der relevanten Information aus Bildern oder Bildsequenzen. Eine wichtige Komponente dieser Systeme ist die Bildsegmentierung, denn sie bestimmt zu einem großen Teil die Qualitaet des Gesamtsystems. Fuer die Segmentierung von Bildern und Bildsequenzen werden neue Algorithmen vorgeschlagen. Das Konzept der Multiresolution wird als eigenstaendig dargestellt, es existiert unabhaengig von der Wavelet-Transformation. Die Wavelet-Transformation wird zur Verarbeitung von Bildern und Bildsequenzen zu einer 2D- bzw. 3D-Wavelet- Transformation erweitert. Fuer die Segmentierung von Bildern wird der Algorithmus Resolution Mosaic Expectation Maximization (RM-EM) vorgeschlagen. Das Ergebnis der Vorverarbeitung sind unterschiedlich aufgeloesten Teilbilder, das Aufloesungsmosaik. Durch dieses Mosaik lassen sich raeumliche Korrelationen zwischen den Pixeln ausnutzen. Die Verwendung unterschiedlicher Aufloesungen beschleunigt die Verarbeitung und verbessert die Ergebnisse. Fuer die Extraktion von bewegten Objekten aus Bildsequenzen werden neue Algorithmen vorgeschlagen, die auf der 3D-Wavelet-Transformation und auf der Analyse mit 3D-Wavelet-Packets beruhen. Die neuen Algorithmen haben den Vorteil, dass sie sowohl die raeumlichen als auch die zeitlichen Bewegungsinformationen beruecksichtigen. Wegen der geringen Berechnungskomplexitaet der Wavelet-Transformation ist fuer den ersten Segmentierungsschritt Hardware auf der Basis von FPGA entworfen worden. Aktuelle Anwendungen werden genutzt, um die Algorithmen zu evaluieren: die Segmentierung von Magnetresonanzbildern des menschlichen Gehirns und die Detektion von bewegten Objekten in Bildsequenzen von Verkehrsszenen. Die neuen Algorithmen sind robust und fuehren zu besseren Segmentierungsergebnissen.More and more computer vision systems take part in the automation of various applications. The main task of such systems is to automate the process of visual recognition and to extract relevant information from the images or image sequences acquired or produced by such applications. One essential and critical component in almost every computer vision system is image segmentation. The quality of the segmentation determines to a great extent the quality of the final results of the vision system. New algorithms for image and video segmentation based on the multiresolution analysis and the wavelet transform are proposed. The concept of multiresolution is explained as existing independently of the wavelet transform. The wavelet transform is extended to two and three dimensions to allow image and video processing. For still image segmentation the Resolution Mosaic Expectation Maximization (RM-EM) algorithm is proposed. The resolution mosaic enables the algorithm to employ the spatial correlation between the pixels. The level of the local resolution depends on the information content of the individual parts of the image. The use of various resolutions speeds up the processing and improves the results. New algorithms based on the 3D wavelet transform and the 3D wavelet packet analysis are proposed for extracting moving objects from image sequences. The new algorithms have the advantage of considering the relevant spatial as well as temporal information of the movement. Because of the low computational complexity of the wavelet transform an FPGA hardware for the primary segmentation step was designed. Actual applications are used to investigate and evaluate all algorithms: the segmentation of magnetic resonance images of the human brain and the detection of moving objects in image sequences of traffic scenes. The new algorithms show robustness against noise and changing ambient conditions and gave better segmentation results.
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Kim, Yong Ku. "Bayesian multiresolution dynamic models." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180465799.
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Reyes-Aldasoro, Constantino Carlos. "Multiresolution volumetric texture segmentation." Thesis, University of Warwick, 2004. http://wrap.warwick.ac.uk/67756/.
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This thesis investigates the segmentation of data in 2D and 3D by texture analysis using Fourier domain filtering. The field of texture analysis is a well-trodden one in 2D, but many applications, such as Medical Imaging, Stratigraphy or Crystallography, would benefit from 3D analysis instead of the traditional, slice-by-slice approach. With the intention of contributing to texture analysis and segmentation in 3D, a multiresolution volumetric texture segmentation (M-VTS) algorithm is presented. The method extracts textural measurements from the Fourier domain of the data via sub-band filtering using a Second Orientation Pyramid. A novel Bhattacharyya space, based on the Bhattacharyya distance is proposed for selecting of the most discriminant measurements and produces a compact feature space. Each dimension of the feature space is used to form a Quad Tree. At the highest level of the tree, new positional features are added to improve the contiguity of the classification. The classified space is then projected to lower levels of the tree where a boundary refinement procedure is performed with a 3D equivalent of butterfly filters. The performance of M-VTS is tested in 2D by classifying a set of standard texture images. The figures contain different textures that are visually stationary. M-VTS yields lower misclassification rates than reported elsewhere ([104, 111, 124]). The algorithm was tested in 3D with artificial isotropic data and three Magnetic Resonance Imaging sets of human knees with satisfactory results. The regions segmented from the knees correspond to anatomical structures that could be used as a starting point for other measurements. By way of example, we demonstrate successful cartilage extraction using our approach.
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Baker, Jonathan D. (Jonathan Daniel). "Multiresolution statistical object recognition." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/37721.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 105-108).
by Jonathan D. Baker.
M.S.
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Bobichon, Yves. "Restauration d'image en multiresolution." Nice, 1997. http://www.theses.fr/1997NICE5090.
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La restauration est un pretraitement indispensable a l'exploitation scientifique des images. Elle vise a obtenir une image de haute qualite a partir de donnees degradees. Cette these traite du filtrage des images radar a ouverture synthetique (ros) et de la restauration des images astronomiques comprimees avec pertes. Pour le filtrage du bruit de speckle dans les images ros. Nous avons propose une methode multi-echelles basee sur une transformation en ondelettes non decimee. La resolution geometrique de l'image est ainsi preservee, et grace a une transformation quadratique prealable des donnees, l'estimation de la radiometrie a partir de l'image filtree est optimale. Contrairement aux filtres homomorphiques, cette transformation n'elimine pas le caractere multiplicatif du speckle, ce qui nous a conduit a mener une etude originale sur le filtrage d'un tel bruit dans un espace multi-echelles. La decompression d'une image comprimee avec pertes peut etre vue comme un probleme de restauration d'image dont le but est de restituer une partie de l'information perdue. Nous avons propose un algorithme de compresssion pour les images astronomiques, qui concentre en priorite les pertes sur les structures non significatives. Cependant, pour des taux de compression eleves, la perte d'information est inevitable. Nous avons developpe une methode de restauration qui considere la decompression d'une image comprimee avec pertes, comme la resolution d'un probleme inverse sous contraintes. Une contrainte de douceur ameliore la qualite visuelle de l'image et les mesures astrometriques et photometriques effectuees sur les objets sont plus precises. Neanmoins, une telle contrainte ne permet pas de restituer les structures complexes liees a la fonction d'etalement (psf) du telescope. Nous avons propose une methode de restauration, qui utilise la psf comme contrainte supplementaire, et dans laquelle sont couples le filtrage, la compression et la deconvolution dans un cadre multiresolution.
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Novaes, Marcos (Marcos Nogueira). "Multiresolution Signal Cross-correlation." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc277645/.
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Signal Correlation is a digital signal processing technique which has a wide variety of applications, ranging from geophysical exploration to acoustic signal enhancements, or beamforming. This dissertation will consider this technique in an underwater acoustics perspective, but the algorithms illustrated here can be readily applied to other areas. Although beamforming techniques have been studied for the past fifty years, modern beamforming systems still have difficulty in operating in noisy environments, especially in shallow water.
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Alchorbaji-Mzaik, Mohammad Tahsin. "Multiresolution architectures and algorithms /." The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487849696966974.
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Schiavazzi, Daniele. "Redundant Multiresolution Uncertainty Propagation." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3422585.
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Stochastic partial differential equations can be efficiently solved using collocation approaches combined with polynomial expansion in parameter space. Estimators based on these concepts show smaller variance than traditional or stratified Monte Carlo approaches under mild dimensionality. Research efforts in this context are focused on improving the efficiency of these methodologies for high dimensional problems (increasing number of input random variables) or for problems with discontinuous response in parameter space. In the present work, we use Compressive Sampling in order to minimize the number of deterministic computations needed to evaluate expansion coefficients for stochastic responses which are sparse in selected dictionaries of basis. Moreover, multiresolution approximation techniques are extended in the context of non-intrusive uncertainty propagation. Finally, an adaptive Importance Sampling strategy is used where samples are iteratively added to locations containing relevant features of increasingly smaller size. Applications are presented for analytical functions, stochastic differential equations, dynamical systems whose response is discontinuous or characterized by large gradients. Engineering problems involving robust optimization of windmill airfoils and passive damping of structures under uncertainty are also discussed. The last Chapter is devoted to methodologies aiming to restore element conservativeness for numerical and experimental velocity fields.Metodi non intrusivi basati sull’espansione della risposta di un dato sistema nello spazio dei parametri (Chaos expansion methods) consentono di risolvere equazioni differenziali stocastiche con un numero di soluzioni deterministiche minori rispetto ad approcci tradizionali alla Monte Carlo con campionamento classico o stratificato. In tale ambito gli sforzi di ricerca odierni sono volti allo sviluppo di metodologie atte alla riduzione del costo computazionale in problemi caratterizzati da alta dimensionalitá (numero significativo di variabili aleatorie in input) ed al trattamento di problemi con risposta discontinua nello spazio dei parametri. La ricerca condotta si é concentrata sull’utilizzo di recenti tecniche di Compressive Sampling per la minimizzazione del numero di soluzioni deterministiche necessarie alla ricostruzione di risposte dotate di sparsitá secondo un pre-definito dizionario di basi. Inoltre, tecniche di approssimazione multi-risoluzione sono state estese a metodologie non intrusive di propagazione dell’incertezza. Infine, tecniche di Importance Sampling sono state utilizzate per determinare in modo adattativo l’ubicazione di nuovi samples al fine di cogliere le scale maggiormente importanti nelle risposte approssimate. Le metodologie approfondite ed implementate nell’ambito della ricerca svolta sono state applicate ad un insieme di funzioni analitiche, sistemi descritti da equazioni differenziali stocastiche, sistemi dinamici con risposte caratterizzate da elevati gradienti o discontinuitá, problemi ingegneristici con particolare riferimento all’ottimizzazione robusta della performance aerodinamica di profili per pale eoliche e sistemi passivi di smorzamento delle vibrazioni operanti sotto incertezza. Vengono inoltre presentate metodologie atte a ripristinare doti di conservazione di massa in flussi numerici e sperimentali.
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Bonneau, Georges-Pierre. "Multiresolution pour la Visualisation Scientifique." Habilitation à diriger des recherches, Université de Grenoble, 2000. http://tel.archives-ouvertes.fr/tel-01064669.
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Les travaux de recherche dont ce mémoire est l'objet sont dédiés à la visualisation à différents niveaux de détail de données scientifiques. Les données scientifiques abordées sont de deux types. Les premières sont définies sur des grilles tridimensionnelles uniformes; le domaine d'application correspondant étant alors la visualisation de données d'origines médicales provenant de coupes tomographiques ou de scanners IRM. Les secondes sont définies sur des réseaux triangulaires irréguliers, planaires ou sphériques; les domaines d'applications correspondants étant entre autres la visualisation de données topographiques (terrain visualization), ou encore de données provenant de calculs par éléments finis.
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Ghouti, L. "Multiresolution-based digital multimedia watermarking." Thesis, Queen's University Belfast, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426701.
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Panicciari, Tommaso. "Multiresolution tomography for the ionosphere." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.698998.
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The ionosphere is a dynamic and ionized medium. Specification of the ionospheric electron density is important for radio systems operating up to a few GHz. Such systems include communication, navigation and surveillance operations. Computerized Ionospheric Tomography (CIT) is a technique that allows specification of the electron density in the ionosphere. CIT, unlike medical tomography, has geometric limitations such as uneven and sparse distribution of ground-based receivers and limited-angle observations. The inversion is therefore underdetermined and to overcome the geometric limitations of the problem, regularization techniques need to be used. In this thesis the horizontal variation of the ionosphere is represented using wavelet basis functions. Wavelets are chosen because the ground based ionospheric instrumentation is unevenly distributed and hence there is an expectation that the resolution of the tomographic image will change across a large region of interest. Wavelets are able to represent structures with different scale and position efficiently, which is known as Multi Resolution Analysis (MRA). The theory of sparse regularization allows the usage of a small number of basis functions with minimum loss of information. Furthermore, sparsity through wavelets can better differentiate between noise and actual information. This is advantageous because it increases the efficacy to resolve the structures of the ionosphere at different spatial horizontal scale sizes. The basis set is also extended to incorporate time dependence in the tomographic images by means of three-dimensional wavelets. The methods have been tested using both simulated and real observations from the Global Navigation Satellite System (GNSS). The simulation was necessary in order to have a controllable environment where the ability to resolve different scale structures would be tested. The further analysis of the methods required also the use of real observations. They tested the technique under conditions of temporal dynamics that would be more difficult to reproduce with simulations, which often tend to be valid in quiet ionospheric behaviors. Improvements in the detection and reconstruction of ionospheric structures were illustrated with sparse regularization. The comparison was performed against two standard methods. The first one was based on spherical harmonics in space, whilst the second relied on a time-dependent smoothing regularization. In simulation, wavelets showed the possibility to resolve small-scale structures better than spherical harmonics and illustrated the potential of creating ionospheric maps at high resolution. In reality, GNSS satellite orbits allow satellite to receiver datasets that traverse the ionosphere at a few hundred km per second and hence a long time window of typically half an hour may be required to provide observations. The assumption of an unchanging ionosphere is only valid at some locations under very quiet geomagnetic conditions and at certain times of day. For this reason the theory was extended to include time dependence in the wavelet method. This was obtained by considering two approaches: a time-smooth regularization and three-dimensional wavelets. The wavelet method was illustrated on a European dataset and demonstrated some improvements in the reconstructions of the main trough. In conclusion wavelets and sparse regularization were demonstrated to be a valid alternative to more standard methods.
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Brennan, Victor L. "Principal component analysis with multiresolution." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7079/brennan%5Fdissertation.pdf.
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Thesis (Ph. D.)--University of Florida, 2001.Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also contains graphics. Vita. Includes bibliographical references (p. 120-123).
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Clippingdale, Simon. "Multiresolution image modelling and estimation." Thesis, University of Warwick, 1988. http://wrap.warwick.ac.uk/109834/.
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Multiresolution representations make explicit the notion of scale in images, and facilitate the combination of information from different scales. To date, however, image modelling and estimation schemes have not exploited such representations and tend rather to be derived from two- dimensional extensions of traditional one-dimensional signal processing techniques. In the causal case, autoregressive (AR) and ARMA models lead to minimum mean square error (MMSE) estimators which are two-dimensional variants of the well-established Kalman filter. Noncausal approaches tend to be transform-based and the MMSE estimator is the two- dimensional Wiener filter. However, images contain profound nonstationarities such as edges, which are beyond the descriptive capacity of such signal models, and defects such as blurring (and streaking in the causal case) are apparent in the results obtained by the associated estimators. This thesis introduces a new multiresolution image model, defined on the quadtree data structure. The model is a one-dimensional, first-order gaussian martingale process causal in the scale dimension. The generated image, however, is noncausal and exhibits correlations at all scales unlike those generated by traditional models. The model is capable of nonstationary behaviour in all three dimensions (two position and one scale) and behaves isomorphically but independently at each scale, in keeping with the notion of scale invariance in natural images. The optimal (MMSE) estimator is derived for the case of corruption by additive white gaussian noise (AWGN). The estimator is a one-dimensional, first-order linear recursive filter with a computational burden far lower than that of traditional estimators. However, the simple quadtree data structure leads to aliasing and 'block' artifacts in the estimated images. This could be overcome by spatial filtering, but a faster method is introduced which requires no additional multiplications but involves the insertion of some extra nodes into the quadtree. Nonstationarity is introduced by a fast, scale-invariant activity detector defined on the quadtree. Activity at all scales is combined in order to achieve noise rejection. The estimator is modified at each scale and position by the detector output such that less smoothing is applied near edges and more in smooth regions. Results demonstrate performance superior to that of existing methods, and at drastically lower computational cost. The estimation scheme is further extended to include anisotropic processing, which has produced good results in image restoration. An orientation estimator controls anisotropic filtering, the output of which is made available to the image estimator.
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Kpalma, Kidiyo. "Analyse fractale de textures naturelles dans un contexte multiresolution. Application a la segmentation d'images multiresolution." Rennes, INSA, 1992. http://www.theses.fr/1992ISAR0001.
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Cette these est consacree a l'etude des textures naturelles en vue de leur caracterisation pour la segmentation des images dans le contexte de la multiresolution. Apres une exploration des methodes existantes en analyse de textures, une large introduction sur les fractales et leurs proprietes et apres une etude approfondie de la pyramide gaussienne (pyramide passe-bas) qui nous permet d'obtenir des images a resolution variable, nous procedons a l'etude de certaines textures naturelles de l'album de brodatz afin d'en extraire quelques attributs. Avec le parametre fractal h comme signature de la texture, grace a une analyse suivant differentes orientations, on obtient un vecteur attribut par niveau de pyramide. Une seconde methode de caracterisation fractale basee sur la dimension fractale et la lacunarite mesurees a l'aide de la methode des boites est presentee. Deux algorithmes de segmentation d'images multi-echelles sont alors developpes relativement a la facon dont le vecteur attribut est utilise et a partir d'un classifieur de bayesien supervise: 1) l'algorithme de segmentation multiresolution (asm) combine les vecteurs attributs des differents niveaux de la pyramide en un seul vecteur caracteristique pour le transmettre a un processus de classification, 2) l'algorithme de segmentation hierarchique (ash) qui segmente le niveau considere en utilisant le vecteur attribut correspondant. Dans cet algorithme, on utilise l'indice de classification qui mesure le taux de confiance que l'on peut accorder a la classification d'un point et on rejette les points dont l'indice de classification est inferieur a un seuil. Les points rejetes sont alors repris pour une segmentation ulterieure au niveau suivant de la pyramide. A travers les resultats de segmentation obtenus sur des mosaiques de textures dans une structure pyramidale d'une part et des images de texture de scenes naturelles d'autre part, ces methodes se revelent prometteuses. Pour finir, une methode originale d'analyse de textures est proposee. Cette methode qui etudie la distribution du signal de luminance dans un voisinage donne renseigne sur la taille et la forme des primitives dans la texture
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Ripollés, Mateu Oscar Enrique. "Towards a multiresolution model on GPU." Doctoral thesis, Universitat Jaume I, 2009. http://hdl.handle.net/10803/10486.
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El objetivo principal de esta tesis es presentar un conjunto de técnicas que se han desarrollado para mejorar la visualización en tiempo real de mallas poligonales. Se describen varias soluciones a la gestión del nivel de detalle, haciendo énfasis en la explotación del hardware grafico actual. En consecuencia, las contribuciones optimizan el coste de almacenamiento, reducen el tiempo de extracción y minimizan los datos transferidos a través del BUS. Por último, se presenta una solución que es capaz de gestionar el nivel de detalle completamente en la tarjeta gráfica, reduciendo al máximo el tráfico de datos y ofreciendo tanto resoluciones uniformes como variables. Además, este último método ofrece una fácil implementación en aplicaciones 3D que permiten la aplicación de shaders a mallas poligonales.
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Prasher, Sham. "Query processing in multiresolution spatial databases /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18682.pdf.
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Beuchler, Sven, Reinhold Schneider, and Christoph Schwab. "Multiresolution weighted norm equivalences and applications." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200600503.
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We establish multiresolution norm equivalences in
weighted spaces L2w((0,1))
with possibly singular weight functions w(x)≥0
in (0,1).
Our analysis exploits the locality of the
biorthogonal wavelet basis and its dual basis
functions. The discrete norms are sums of wavelet
coefficients which are weighted with respect to the
collocated weight function w(x) within each scale.
Since norm equivalences for Sobolev norms are by now
well-known, our result can also be applied to
weighted Sobolev norms. We apply our theory to
the problem of preconditioning p-Version FEM
and wavelet discretizations of degenerate
elliptic problems.
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Li, Zuofa. "Multiresolution approximation in gravity field modeling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq20749.pdf.
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Pradhan, Pushkar S. "Multiresolution based, multisensor, multispectral image fusion." Diss., Mississippi State : Mississippi State University, 2005. http://library.msstate.edu/etd/show.asp?etd=etd-07082005-140541.
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Akhlaghian, Tab Fardin. "Multiresolution scalable image and video segmentation." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060227.100704/index.html.
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Cesbron, Fred́eŕique Chantal. "Multiresolution fractal coding of still images." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/15508.
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Nicholl, P. R. "Face recognition using multiresolution statistical approaches." Thesis, Queen's University Belfast, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517434.
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Kalmbach, Mark Russell. "Wavelet-based multiresolution analyses of signals." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23812.
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Scott, Hugh R. R. "Multiresolution techniques for audio signal restoration." Thesis, University of Warwick, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307347.
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Mashikian, Paul Stephan. "Multiresolution models of financial time series." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43483.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaves 89-92).
by Paul Stephan Mashikian.
M.Eng.
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Carter, Duane B. "Analysis of Multiresolution Data fusion Techniques." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36609.
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In recent years, as the availability of remote sensing imagery of varying resolution has increased, merging images of differing spatial resolution has become a significant operation in the field of digital remote sensing. This practice, known as data fusion, is designed to enhance the spatial resolution of multispectral images by merging a relatively coarse-resolution image with a higher resolution panchromatic image of the same geographic area. This study examines properties of fused images and their ability to preserve the spectral integrity of the original image. It analyzes five current data fusion techniques for three complex scenes to assess their performance. The five data fusion models used include one spatial domain model (High-Pass Filter), two algebraic models (Multiplicative and Brovey Transform), and two spectral domain models (Principal Components Transform and Intensity-Hue-Saturation). SPOT data were chosen for both the panchromatic and multispectral data sets. These data sets were chosen for the high spatial resolution of the panchromatic (10 meters) data, the relatively high spectral resolution of the multispectral data, and the low spatial resolution ratio of two to one (2:1). After the application of the data fusion techniques, each merged image was analyzed statistically, graphically, and for increased photointerpretive potential as compared with the original multispectral images. While all of the data fusion models distorted the original multispectral imagery to an extent, both the Intensity-Hue-Saturation Model and the High-Pass Filter model maintained the original qualities of the multispectral imagery to an acceptable level. The High-Pass Filter model, designed to highlight the high frequency spatial information, provided the most noticeable increase in spatial resolution.Master of Science
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Srinivas, Sushma. "DETECTING VULNERABLE PLAQUES WITH MULTIRESOLUTION ANALYSIS." Cleveland State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=csu1326932229.
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Gregorski, Benjamin F. "Multiresolution tetrahedral meshes for scientific visualization /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.
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Peyton, William M. "Multiresolution image recognition using the wavelet transform." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA316566.
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Thesis (M.S. in Electrical Engineering and Electrical Engineer) Naval Postgraduate School, June 1996.Thesis advisor(s): Murali Tummala. "June 1996." Includes bibliographical references. Also Available online.
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Pedersoli, Marco. "Hierarchical multiresolution models for fast object detection." Doctoral thesis, Universitat Autònoma de Barcelona, 2012. http://hdl.handle.net/10803/286175.
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Dia a dia, la capacitat de detectar i reconèixer objectes en imatges automàticament es fa cada vegada més important. Des dels sistemes de seguretat i robots, als telèfons d'última generació i la realitat augmentada, tot dispositiu intel·ligent necessita conèixer el significat semàntic de la imatge.
Aquesta tesi aborda el problema de la detecció ràpida d'objectes a partir de models basats en patrons. La cerca d'un objecte en imatges s'implementa evaluant la similitud entre el model i cada ubicació i escala possibles en una imatge.
Aquí s'argumenta que utilitzar una representació d'objectes basada en una jerarquia de múltiples resolucions és una opció adequada que pot conduir a una excel·lent precisió i un càlcul molt ràpid. Com, per detectar a múltiples escales, la cerca de l'objecte s'efectua de forma implícita a múltiples resolucions, el fet d'utilitzar un model en múltiples resolucions permet una millor representació de l'objecte, gairebé sense cost computacional addicional. A més, un model multiresolució s'adapta de forma natural a una cerca també en múltiples resolucions en la imatge, des de baixes a altes. Això ens porta a un conjunt d'acceleracions importants, degut a que es poden limitar el conjunt d'ubicacions on fer la cerca de l'objecte a nivells baixos de resolució, el que comporta un cost més reduït en l'avaluació del model.
Una cerca jeràrquica de baixes a altes resolucions es pot fer utilizant una cascada de classificadors multiresolució, que elimina facils hipòtesis neagatives utilizant la baixa resolució. %basades en la probabilitat trobada en cada lloc on es fa la detecció,
Un mètode alternatiu es basa en seleccionar localment, però de manera uniforme, les ubicacions de detecció a resolució baixa y propagarles fins a la resolució més alta. Aquest enfocament alternatiu, que llamem cerca coarse-to-fine, té una acceleració i rendiments semblants a la cascada de múltiples resolucions, però en un temps de computació independent del contingut de la imatge.
La cerca coarse-to-fine s'ha estès a models deformables amb partes. En aquest enfocament, la jerarquia dels models se separa de forma recursiva en les subparts deformables de l'objecte a mesura que augmentem la resolució del model. D'aquesta manera, cada part s'ajusta a l'objecte en la imatge, produint una millor representació i, per tant una millor precisió en la detecció, juntament amb un temps computacional molt reduït.
S'han validat els diferents models de multiresolució en diverses bases de dades conegudes i d'ús comú, mostrant que els resultats arriben a l'estat de l'art, però amb un cost computacional molt reduït. Finalment, es presenta una especialització d'aquest model multiresolució deformable per la tasca de detecció de vianants des de vehicles en moviment, que requereix tant una alta precisió com que el rendiment sigui en temps real. S'ha demostrat que la qualitat global del model proposat és superior als treballs anteriors i que té un grau de detecció de vianants fiable i ràpid utilitzant únicament informació de la imatge.Día a día, la capacidad de detectar y reconocer objetos en imágenes automáticamente se hace cada vez más importante. Desde los sistemas de seguridad y los robots, a los teléfonos de última generación y la realidad aumentada, cada dispositivo inteligente necesita conocer el significado semántico de la imagen. Esta tesis aborda el problema de la detección rápida de objetos a partir de modelos basados en patrones. La búsqueda de un objeto en una imagen es el procedimiento de evaluar la similitud entre el modelo y cada ubicación y escala posible de la imagen. En esta tesis se argumenta que utilizar una representación del modelo de objetos basada en una jerarquía de resoluciones múltiples es una opción adecuada que puede conducir a una excelente precisión y un cálculo rápido. Como, para detectar a múltiples escalas, la búsqueda del objeto se efectúa de forma implícita en múltiples resoluciones, utilizar también un modelo de objetos con resoluciones múltiples permite una representación mejor del modelo, casi sin coste computacional adicional. Además, el modelo multiresolución se adapta de forma natural a una búsqueda sobre multiples resoluciones en la imagen, desde bajas a altas. Esto conduce a una doble aceleración debida a: un inicialmente reducido conjunto de ubicaciones en baja resolución donde realizar la búsqueda del objeto; un coste reducido de la evaluación del modelo. La búsqueda sobre multiples resoluciones puede efectuarse utilizando una cascada de clasificadores multirresolución, que elimina los ejemplos negativos en la resolución baja. Un método alternativo se basa en seleccionar localmente, pero de manera uniforme, las mejores detecciones a resolución baja y, luego, propagar estas hipothesis a los siguientes niveles de resolución. Este método, que llamamos búsqueda coarse-to-fine, tiene una aceleración parecida a la cascada de multiples resoluciones, pero el coste computacional es independiente del contenido de la imagen. La búsqueda coarse-to-fine se extiende a modelos deformables con partes. En este enfoque, la jerarquía de los modelos se separa de forma recursiva en las subpartes deformables a medida que aumenta la resolución del modelo. De esta manera, cada parte puede ajustarse al objecto en la imagen, produciendo una mejor representación y, por tanto, una mejor precisión en la detección con un tiempo computacional muy reducido. Se han validado los diferentes modelos de multirresolución en varias bases de datos de uso común, mostrando que los resultados alcanzan el estado del arte, pero con un coste computacional reducido. Por último, se presenta una especialización del modelo de multirresolución deformable para la tarea de detección de peatones desde vehículos en movimiento, que requiere tanto una alta precisión como un rendimiento en tiempo real. Se ha demostrado que la calidad global de nuestro modelo es superior a los trabajos anteriores y que puede producir una detección fiable de peatones basada solamente en imágenes.
Day by day, the ability to automatically detect and recognize objects in unconstrained images is becoming more and more important. From security systems and robots, to smart phones and augmented reality, every intelligent device needs to know the semantic meaning of an image. This thesis tackles the problem of fast object detection based on template models. Searching for an object in an image is the procedure of evaluating the similarity between the template model and every possible image location and scale. %the likelihood of the presence of that object. Here we argue that using a template model representation based on a multiple resolution hierarchy is an optimal choice that can lead to excellent detection accuracy and fast computation. As the search of the object is implicitly effectuated at multiple image resolutions to detect objects at multiple scales, using also a template model with multiple resolutions permits an improved model representation almost without any additional computational cost. Also, the hierarchy of multiple resolutions naturally adapts to a search over image resolutions, from coarse to fine. This leads to a double speed-up due to: an initially reduced set of coarse locations where to search for the object; a lower cost of evaluating the template model. The search over resolutions can be effectuated by using a cascade of multiresolution classifiers, which saves computation by early stopping the search at coarse level when finding easy negative examples. %pruning hypotheses based on the likelihood of each detection location, which leads to a cascade of multiresolution classifiers. An alternative approach is to locally but uniformly selecting the most promising detection locations at coarse level and, then, iteratively propagate only these ones to the finer resolutions, saving computation. This procedure, that we call coarse-to-fine search, has a speed-up similar to the multiresolution cascade, but a computational time independent of the image content. The coarse-to-fine search is then extended to deformable parts models. In this approach, as increasing the model resolution, the hierarchy of models is recursively separated into deformable subparts. In this way, each part can be aligned to the object in the image, producing a better representation and, therefore, an improved detection accuracy with still a reduced computational cost. We validate the different multiresolution models on several commonly used datasets, showing state-of-the-art results with a reduced computational cost. Finally, we specialize the multiresolution deformable model to the challenging task of pedestrian detection on moving vehicles, that requires both high accuracy and real-time performance. We show that the overall quality of our model is superior to previous works and it can lead to the first reliable pedestrian detection based only on images.
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Ghavamnia, Seyed Mohammad H. "Direct rendering of multiresolution decomposed volume data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ35820.pdf.
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Cui, Qingguang. "Measuring data abstraction quality in multiresolution visualizations." Worcester, Mass. : Worcester Polytechnic Institute, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-041107-224152/.
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Malassenet, Francois Jacques. "Self-Affine signals and weighted multiresolution processes." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/14914.
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Zheng, Bibo. "Multiresolution fixation of a binocular vision system." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-07112009-040450/.
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Au, Kin Chung. "Sampling-sensitive multiresolution hierarchy for irregular meshes /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20AU.
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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.Includes bibliographical references (leaves 57-59). Also available in electronic version. Access restricted to campus users.
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Hamlett, Neil A. "Comparison of multiresolution techniques for digital signal processing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from the National Technical Information Service, 1993. http://edocs.nps.edu/npspubs/scholarly/theses/1993/Mar/93Mar_Hamlett.pdf.
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Romero, Juan R. "Generalized multiresolution analysis construction and measure theoretic characterization /." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2942.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.Thesis research directed by: Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Zhao, Fangwei. "Multiresolution analysis of ultrasound images of the prostate." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2004.0028.
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[Truncated abstract] Transrectal ultrasound (TRUS) has become the urologist’s primary tool for diagnosing and staging prostate cancer due to its real-time and non-invasive nature, low cost, and minimal discomfort. However, the interpretation of a prostate ultrasound image depends critically on the experience and expertise of a urologist and is still difficult and subjective. To overcome the subjective interpretation and facilitate objective diagnosis, computer aided analysis of ultrasound images of the prostate would be very helpful. Computer aided analysis of images may improve diagnostic accuracy by providing a more reproducible interpretation of the images. This thesis is an attempt to address several key elements of computer aided analysis of ultrasound images of the prostate. Specifically, it addresses the following tasks: 1. modelling B-mode ultrasound image formation and statistical properties; 2. reducing ultrasound speckle; and 3. extracting prostate contour. Speckle refers to the granular appearance that compromises the image quality and resolution in optics, synthetic aperture radar (SAR), and ultrasound. Due to the existence of speckle the appearance of a B-mode ultrasound image does not necessarily relate to the internal structure of the object being scanned. A computer simulation of B-mode ultrasound imaging is presented, which not only provides an insight into the nature of speckle, but also a viable test-bed for any ultrasound speckle reduction methods. Motivated by analysis of the statistical properties of the simulated images, the generalised Fisher-Tippett distribution is empirically proposed to analyse statistical properties of ultrasound images of the prostate. A speckle reduction scheme is then presented, which is based on Mallat and Zhong’s dyadic wavelet transform (MZDWT) and modelling statistical properties of the wavelet coefficients and exploiting their inter-scale correlation. Specifically, the squared modulus of the component wavelet coefficients are modelled as a two-state Gamma mixture. Interscale correlation is exploited by taking the harmonic mean of the posterior probability functions, which are derived from the Gamma mixture. This noise reduction scheme is applied to both simulated and real ultrasound images, and its performance is quite satisfactory in that the important features of the original noise corrupted image are preserved while most of the speckle noise is removed successfully. It is also evaluated both qualitatively and quantitatively by comparing it with median, Wiener, and Lee filters, and the results revealed that it surpasses all these filters. A novel contour extraction scheme (CES), which fuses MZDWT and snakes, is proposed on the basis of multiresolution analysis (MRA). Extraction of the prostate contour is placed in a multi-scale framework provided by MZDWT. Specifically, the external potential functions of the snake are designated as the modulus of the wavelet coefficients at different scales, and thus are “switchable”. Such a multi-scale snake, which deforms and migrates from coarse to fine scales, eventually extracts the contour of the prostate
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Yang, Qingde. "Multiresolution analysis on non-abelian locally compact groups." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0018/NQ43523.pdf.
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Zhao, Fangwei. "Multiresolution analysis of ultrasound images of the prostate /." Connect to this title, 2003. http://theses.library.uwa.edu.au/adt-WU2004.0028.
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Li, Chang-Tsun. "Unsupervised texture segmentation using multiresolution Markov random fields." Thesis, University of Warwick, 1998. http://wrap.warwick.ac.uk/39307/.
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In this thesis, a multiresolution Markov Random Field (MMRF) model for segmenting textured images without supervision is proposed. Stochastic relaxation labelling is adopted to assign the class label with highest probability to the block (site) being visited. Class information is propagated from low spatial resolution to high spatial resolution, via appropriate modifications to the interaction energies defining the field, to minimise class-position uncertainty. The thesis contains novel ideas presented in Chapter 4 and 5, respectively. In Chapter 4, the Multiresolution Fourier Transform (MFT) is used to provide a set of spatially localised texture descriptors, which are based on a two-component model of texture, in which one component is a deformation, representing the structural or deterministic elements and the other is a stochastic one. Experiments show that the algorithm is efficient in alleviating class-position uncertainty via data propagation across resolutions. However, the blocking artifacts of the segmentation results show that it is preferable to combine both class and position information so as to achieve smoother and more accurate boundary estimation. In Chapter 5, based on the same MFT-MMRF framework, a boundary process is proposed to refine the segmentation result of the region process proposed in Chapter 4. At each resolution, all the image blocks on either sides of the preliminary boundary detected in the region process are treated as potential boundary-containing blocks (PBCB's). The orientation and the centroid of the boundary-segment contained in each PBCB are calculated. The sequence of PBCB's are then modelled as a MRF and the interaction energy between each pair of neighbouring blocks is defined as a function of the 'distance' D between the centroids of the two boundary segments. During the stochastic relaxation process boundary/non-boundary labels are assigned to the PBCB's. Once the algorithm converges, the centroids of the identified true boundary blocks are connected to form the refined boundary which is propagated down to the next resolution for further refinement.
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Davies, Andrew Richard. "Image feature analysis using the Multiresolution Fourier Transform." Thesis, University of Warwick, 1993. http://wrap.warwick.ac.uk/50490/.
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The problem of identifying boundary contours or line structures is widely recognised as an important component in many applications of image analysis and computer vision. Typical solutions to the problem employ some form of edge detection followed by line following or, more commonly in recent years, Hough transforms. Because of the processing requirements of such methods and to try to improve the robustness of the algorithms, a number of authors have explored the use of multiresolution approaches to the problem. Non-parametric, iterative approaches such as relaxation labelling and "Snakes" have also been used. This thesis presents a boundary detection algorithm based on a multiresolution image representation, the Multiresolution Fourier Transform (MFT), which represents an image over a range of spatial/spatial-frequency resolutions. A quadtree based image model is described in which each leaf is a region which can be modelled using one of a set of feature classes. Consideration is given to using linear and circular arc features for this modelling, and frequency domain models are developed for them. A general model based decision process is presented and shown to be applicable to detecting local image features, selecting the most appropriate scale for modelling each region of the image and linking the local features into the region boundary structures of the image. The use of a consistent inference process for all of the subtasks used in the boundary detection represents a significant improvement over the adhoc assemblies of estimation and detection that have been common in previous work. Although the process is applied using a restricted set of local features, the framework presented allows for expansion of the number of boundary feature models and the possible inclusion of models of region properties. Results are presented demonstrating the effective application of these procedures to a number of synthetic and natural images.
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Chen, Guo-Huei. "Image segmentation using a multiresolution random field model." Thesis, University of Warwick, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269395.
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Ismail, Ahmed E. (Ahmed Emad) 1977. "Multiresolution methods for materials modeling via coarse-graining." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/28840.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2005.Includes bibliographical references (p. 209-222).
(cont.) time, while obtaining useful information about the thermodynamic behavior of the system. We show how statistical mechanics can be formulated using the wavelet transform as a coarse-graining technique. For small systems in which exact enumerations of all states is possible, we illustrate how the method recovers reasonably good estimates for physical properties (errors no more than 10%) with several orders of magnitude fewer operations than are required for an exact enumeration. In addition, we illustrate that errors introduced by the wavelet transform vanish in the neighborhood of fixed points of systems as determined by RG theory. Using scaling results from simulations at different length scales, we estimate the thermodynamic behavior of the original system without performing simulations on the full original system. In addition, we make the method adaptive by using fluctuation properties of the system to set criteria under which further coarse graining or refinement of the system is required. We demonstrate our method for the Ising universality class of problems. We also examine the applicability of the WAMC framework to polymer chains. Polymers are quintessential examples of the need for simulations at multiple scales: at one end, we can study short chains using quantum chemistry methods; yet polymers can have relaxation times on the order of seconds or longer, and molecular weights of 10⁶ or more. Even with modern computational resources, simulating behavior at long times or for long chains is still prohibitively expensive ...
Multiscale modeling of physical systems often requires the use of multiple types of simulations to bridge the various length scales that. need to be considered: for example, a density-functional theory at the electronic scale will be combined with a molecular-dynamics simulation at the atomistic level, and with a finite-element method at the macroscopic level. An improvement to this scheme would be a method which is capable of consistently simulating a system at multiple levels of resolution without passing from one simulation type to another, so that different simulations can be studied at a common length scale by appropriate coarse-graining or refinement of a given model. We introduce the wavelet transform as the basis for a new coarse-graining framework. A family of orthonormal basis, the wavelet transform separates data sets, such as spatial coordinates or signal strengths, into subsets representing local averages and local differences. The wavelet transform has several desirable properties for coarse-graining: it is hierarchical, compact, and has natural applications to approximating physical data sets. As a hierarchical method, it can be used to rescale a Hamiltonian to a desired length scale, and at the same time also rescales the particles of the system by creating "blocked" particles in the spirit of renor-malization group (RG) calculations. The wavelet-accelerated Monte Carlo (WAMC) framework performs a Monte Carlo simulations on a small system which will be transformed into a block particle to obtain the probability distribution of the blocked particle; a Monte Carlo simulation is then performed on the resulting system of blocked particles. This method, which can be repeated as needed, can achieve significant speed-ups in computational
by Ahmed E. Ismail.
Ph.D.
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Greer, Donald Reed. "Multiresolution laser radar range profiling of real imagery." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/40181.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 112-113).
by Donald Reed Greer.
M.Eng.