Wavelet estimation in diffusions with periodicity

Wir betrachten einen zeitlich inhomogenen Diffusionsprozess, der durch eine stochastische Differentialgleichung gegeben wird, deren Driftterm ein deterministisches T-periodisches Signal beinhaltet, dessen Periodizität bekannt ist. Dieses Signal sei in einem Besovraum enthalten. Wir schätzen es mit Hilfe eines nichtparametrischen Waveletschätzers. Unser Schätzer ist von einem Wavelet-Dichteschätzer mit Thresholding inspiriert, der 1996 in einem klassischen iid-Modell von Donoho, Johnstone, Kerkyacharian und Picard konstruiert wurde. Unter gewissen Ergodizitätsvoraussetzungen an den Prozess können wir nichtparametrische Konvergenzraten angegeben, die bis auf einen logarithmischen Term den Raten im klassischen iid-Fall entsprechen. Diese Raten werden mit Hilfe von Orakel-Ungleichungen gezeigt, die auf Ergebnissen über Markovketten in diskreter Zeit von Clémencon, 2001, beruhen. Außerdem betrachten wir einen technisch einfacheren Spezialfall und zeigen einige Computersimulationen dieses Schätzers.

Wavetrack, implementazione ottimizzata di un algoritmo di pitch tracking basato su wavelet

WaveTrack é un'implementazione ottimizzata di un algoritmo di pitch tracking basato su wavelet, nello specifico viene usata la trasformata Fast Lifting Wavelet Transform con la wavelet di Haar. La libreria è stata scritta nel linguaggio C e tra le sue peculiarità può vantare tempi di latenza molto bassi, un'ottima accuratezza e una buona flessibilità d'uso grazie ad alcuni parametri configurabili.

Trasformate wavelet

La presente tesi vuole dare una descrizione delle Trasformate Wavelet indirizzata alla codifica dell’immagine in formato JPEG2000. Dopo aver quindi descritto le prime fasi della codifica di un’immagine, procederemo allo studio dei difetti derivanti dall’analisi tramite la Trasformata Discreta del Coseno (utilizzata nel formato predecessore JPEG). Dopo aver quindi descritto l’analisi multirisoluzione e le caratteristiche che la differenziano da quest’ultima, analizzeremo la Trasformata Wavelet dandone solo pochi accenni teorici e cercando di dedurla, in una maniera più indirizzata all’applicazione. Concluderemo la tesi descrivendo la codifica dei coefficienti calcolati, e portando esempi delle innumerevoli applicazioni dell’analisi multirisoluzione nei diversi campi scientifici e di trasmissione dei segnali.

Analyse zur Auswirkung der irreversiblen Wavelet-Kompression (JPEG2000) auf CT-Bildverarbeitungs- und Darstellungsalgorithmen

Der technische Fortschritt konfrontiert die medizinische Bildgebung wie keine andere Sparte der Medizin mit einem rasanten Anstieg zu speichernder Daten. Anschaffung, Wartung und Ausbau der nötigen Infrastruktur entwickeln sich zunehmend zu einem ökonomischen Faktor. Ein Verfahren, welches diesem Trend etwas entgegensetzten könnte ist die irreversible Bilddatenkompression. Sie ist seit über 10 Jahren Gegenstand vieler Studien, deren Ergebnisse sich wiederum in Empfehlungen zum Einsatz irreversibler Kompression mehrerer nationaler und internationaler Organisation, wie CAR, DRG, RCR und ESR wiederspiegeln. Tenor dieser Empfehlungen ist, dass der Einsatz von moderater irreversibler Bilddatenkompression sicher und sinnvoll ist. Teil dieser Empfehlungen sind auch Angaben über das Maß an Kompression, ausgedrückt in Kompressionsraten, welche je nach Untersuchung und anatomischer Region als sicher anwendbar gelten und keinen diagnostisch relevanten Verlust der komprimierten Bilder erzeugen.rnVerschiedene Kompressionsalgorithmen wurden vorgeschlagen. Letztendlich haben sich vor allem die beiden weit verbreiteten Algorithmen JPEG und JPEG2000 bewährt. Letzterer erfährt in letzter Zeit zunehmen Anwendung, aufgrund seiner einfacheren Handhabung und seiner umfangreichen Zusatzfunktionen.rnAufgrund rechtlich-ethischer Bedenken hat die irreversible Kompression keine breite praktische Anwendung finden können. Dafür verantwortlich ist unter anderem auch die Unklarheit, wie sich irreversible Kompression auf Nach- und Weiterverarbeitung (sog. Postprocessing) medizinischer Bilder, wie Segmentierung, Volumetrie oder 3D-Darstellung, auswirkt. Bisherige Studien zu diesem Thema umfassen vier verschiedene Postprocessing-Algorithmen. Die untersuchten Algorithmen zeigten sich bei verlustbehafteter Kompression im Bereich der erwähnten, publizierten Kompressionsraten weitgehend unbeeinflusst. Lediglich die computergestützte Messung von Stenosegraden in der digitalen Koronarangiographie kollidiert mit den in Großbritannien geltenden Empfehlungen. Die Verwendung unterschiedlicher Kompressionsalgorithmen schränkt die allgemeinernAussagekraft dieser Studienergebnisse außerdem ein.rnZur Erweiterung der Studienlage wurden vier weitere Nach- und Weiterverarbeitungsalgorithmen auf ihre Kompressionstoleranz untersucht. Dabei wurden die Kompressionsraten von 8:1, 10:1 und 15:1 verwendet, welche um die empfohlenen Kompressionsraten von CAR, DRG, RCR und ESR liegen und so ein praxisnahes Setting bieten. Als Kompressionsalgorithmus wurde JPEG2000 verwendet, aufgrund seiner zunehmenden Nutzung in Studien sowie seiner bereits erwähnten Vorzüge in Sachen Handhabung und Zusatzfunktionen. Die vier Algorithmen umfassten das 3D-Volume rendering von CT-Angiographien der Becken-Bein-Gefäße, die Computer-assistierte Detektion von Lungenrundherden, die automatisierte Volumetrie von Leberrundherden und die funktionelle Bestimmung der Ejektionsfraktion in computertomographischen Aufnahmen des Herzens.rnAlle vier Algorithmen zeigten keinen Einfluss durch irreversibler Bilddatenkompression in denrngewählten Kompressionsraten (8:1, 10:1 und 15:1). Zusammen mit der bestehenden Literatur deuten die Ergebnisse an, dass moderate irreversible Kompression im Rahmen aktueller Empfehlungen keinen Einfluss auf Nach- und Weiterverarbeitung medizinischer Bilder hat. Eine explizitere Vorhersage zu einem bestimmten, noch nicht untersuchten Algorithmus ist jedoch aufgrund der unterschiedlichen Funktionsweisen und Programmierungen nicht sicher möglich.rnSofern ein Postprocessing Algorithmus auf komprimiertes Bildmaterial angewendet werden soll, muss dieser zunächst auf seine Kompressionstoleranz getestet werden. Dabei muss der Test eine rechtlich-ethische Grundlage für den Einsatz des Algorithmus bei komprimiertem Bildmaterial schaffen. Es sind vor allem zwei Optionen denkbar, die Testung institutsintern, eventuell unter Zuhilfenahme von vorgefertigten Bibliotheken, oder die Testung durch den Hersteller des Algorithmus.

Trasformata di Fourier e trasformata Wavelet

Questo elaborato si concentra sullo studio della trasformata di Fourier e della trasformata Wavelet. Nella prima parte della tesi si analizzano gli aspetti fondamentali della trasformata di Fourier. Si definisce poi la trasformata di Fourier su gruppi abeliani finiti, richiamando opportunamente la struttura di tali gruppi. Si mostra che calcolare la trasformata di Fourier nel quoziente richiede un minor numero di operazioni rispetto a calcolarla direttamente nel gruppo di partenza. L'ultima parte dell'elaborato si occupa dello studio delle Wavelet, dette ondine. Viene presentato quindi il sistema di Haar che permette di definire una funzione come serie di funzioni di Haar in alternativa alla serie di Fourier. Si propone poi un vero e proprio metodo per la costruzione delle ondine e si osserva che tale costruzione è strettamente legata all'analisi multirisoluzione. Un ruolo cruciale viene svolto dall'identità di scala, un'identità algebrica che permette di definire certi coefficienti che determinano completamente le ondine. Interviene poi la trasformata di Fourier che riduce la ricerca dei coefficienti sopra citati, alla ricerca di certe funzioni opportune che determinano esplicitamente le Wavelet. Non tutte le scelte di queste funzioni sono accettabili. Ci sono vari approcci, qui viene presentato l'approccio di Ingrid Daubechies. Le Wavelet costituiscono basi per lo spazio di funzioni a quadrato sommabile e sono particolarmente interessanti per la decomposizione dei segnali. Sono quindi in relazione con l'analisi armonica e sono adottate in un gran numero di applicazioni. Spesso sostituiscono la trasformata di Fourier convenzionale.

Wavelet-denoising of electroencephalogram and the absolute slope method: a new tool to improve electroencephalographic localization and lateralization

OBJECTIVE: In ictal scalp electroencephalogram (EEG) the presence of artefacts and the wide ranging patterns of discharges are hurdles to good diagnostic accuracy. Quantitative EEG aids the lateralization and/or localization process of epileptiform activity. METHODS: Twelve patients achieving Engel Class I/IIa outcome following temporal lobe surgery (1 year) were selected with approximately 1-3 ictal EEGs analyzed/patient. The EEG signals were denoised with discrete wavelet transform (DWT), followed by computing the normalized absolute slopes and spatial interpolation of scalp topography associated to detection of local maxima. For localization, the region with the highest normalized absolute slopes at the time when epileptiform activities were registered (>2.5 times standard deviation) was designated as the region of onset. For lateralization, the cerebral hemisphere registering the first appearance of normalized absolute slopes >2.5 times the standard deviation was designated as the side of onset. As comparison, all the EEG episodes were reviewed by two neurologists blinded to clinical information to determine the localization and lateralization of seizure onset by visual analysis. RESULTS: 16/25 seizures (64%) were correctly localized by the visual method and 21/25 seizures (84%) by the quantitative EEG method. 12/25 seizures (48%) were correctly lateralized by the visual method and 23/25 seizures (92%) by the quantitative EEG method. The McNemar test showed p=0.15 for localization and p=0.0026 for lateralization when comparing the two methods. CONCLUSIONS: The quantitative EEG method yielded significantly more seizure episodes that were correctly lateralized and there was a trend towards more correctly localized seizures. SIGNIFICANCE: Coupling DWT with the absolute slope method helps clinicians achieve a better EEG diagnostic accuracy.

A Wavelet Analysis of Pliopleistocene Climate Indicators: A New View of Periodicity Evolution

Wavelet analysis offers an alternative to Fourier based time-series analysis, and is particularly useful when the amplitudes and periods of dominant cycles are time dependent. We analyse climatic records derived from oxygen isotopic ratios of marine sediment cores with modified Morlet wavelets. We use a normalization of the Morlet wavelets which allows direct correspondence with Fourier analysis. This provides a direct view of the oscillations at various frequencies, and illustrates the nature of the time-dependence of the dominant cycles.

Corporalidades transformadas : Embarazo, parto y puerperio

Fil: Tabak, Graciela. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET); Argentina.

Corporalidades transformadas : Embarazo, parto y puerperio

Fil: Tabak, Graciela. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET); Argentina.

Corporalidades transformadas : Embarazo, parto y puerperio

Fil: Tabak, Graciela. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET); Argentina.

Quality assessment by region in spot images fused by means dual-tree complex wavelet transform

This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet transform (DT-CWT), an effective approach for conducting an analytic and oversampled wavelet transform to reduce aliasing, and in turn reduce shift dependence of the wavelet transform. The proposed scheme includes the definition of a model to establish how information will be extracted from the PAN band and how that information will be injected into the MS bands with low spatial resolution. The approach was applied to Spot 5 images where there are bands falling outside PAN’s spectrum. We propose an optional step in the quality evaluation protocol, which is to study the quality of the merger by regions, where each region represents a specific feature of the image. The results show that DT-CWT based approach offers good spatial quality while retaining the spectral information of original images, case SPOT 5. The additional step facilitates the identification of the most affected regions by the fusion process.

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.

A region based approach to background modeling in a wavelet multi-resolution framework

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-resolution framework. Based on a segmentation of the background, characterization is made for each region independently as a mixture of K Gaussian modes, considering the model of the approximation and detail coefficients at the different wavelet decomposition levels. Background region characterization is updated along time, and the detection of elements of interest is carried out computing the distance between background region models and those of each incoming image in the sequence. The inclusion of the context in the modeling scheme through each region characterization makes the model robust, being able to support not only gradual illumination and long-term changes, but also sudden illumination changes and the presence of strong shadows in the scene

Glottal Parameter Estimation by Wavelet Transform for Voice Biometry

Voice biometry is classically based on the parameterization and patterning of speech features mainly. The present approach is based on the characterization of phonation features instead (glottal features). The intention is to reduce intra-speaker variability due to the `text'. Through the study of larynx biomechanics it may be seen that the glottal correlates constitute a family of 2-nd order gaussian wavelets. The methodology relies in the extraction of glottal correlates (the glottal source) which are parameterized using wavelet techniques. Classification and pattern matching was carried out using Gaussian Mixture Models. Data of speakers from a balanced database and NIST SRE HASR2 were used in verification experiments. Preliminary results are given and discussed.

3D Wavelet-based Fusion Techniques for Biomedical Imaging

Hoy en día las técnicas de adquisición de imágenes tridimensionales son comunes en diversas áreas, pero cabe destacar la relevancia que han adquirido en el ámbito de la imagen biomédica, dentro del cual encontramos una amplia gama de técnicas como la microscopía confocal, microscopía de dos fotones, microscopía de fluorescencia mediante lámina de luz, resonancia magnética nuclear, tomografía por emisión de positrones, tomografía de coherencia óptica, ecografía 3D y un largo etcétera. Un denominador común de todas esas aplicaciones es la constante necesidad por aumentar la resolución y la calidad de las imágenes adquiridas. En algunas de dichas técnicas de imagen tridimensional se da una interesante situación: aunque que cada volumen adquirido no contiene información suficiente para representar el objeto bajo estudio dentro de los parámetros de calidad requeridos por algunas aplicaciones finales, el esquema de adquisición permite la obtención de varios volúmenes que representan diferentes vistas de dicho objeto, de tal forma que cada una de las vistas proporciona información complementaria acerca del mismo. En este tipo de situación es posible, mediante la combinación de varias de esas vistas, obtener una mejor comprensión del objeto que a partir de cada una de ellas por separado. En el contexto de esta Tesis Doctoral se ha propuesto, desarrollado y validado una nueva metodología de proceso de imágenes basada en la transformada wavelet disc¬reta para la combinación, o fusión, de varias vistas con información complementaria de un mismo objeto. El método de fusión propuesto aprovecha la capacidad de descom¬posición en escalas y orientaciones de la transformada wavelet discreta para integrar en un solo volumen toda la información distribuida entre el conjunto de vistas adquiridas. El trabajo se centra en dos modalidades diferentes de imagen biomédica que per¬miten obtener tales adquisiciones multi-vista. La primera es una variante de la micro¬scopía de fluorescencia, la microscopía de fluorescencia mediante lámina de luz, que se utiliza para el estudio del desarrollo temprano de embriones vivos en diferentes modelos animales, como el pez cebra o el erizo de mar. La segunda modalidad es la resonancia magnética nuclear con realce tardío, que constituye una valiosa herramienta para evaluar la viabilidad del tejido miocárdico en pacientes con diversas miocardiopatías. Como parte de este trabajo, el método propuesto ha sido aplicado y validado en am¬bas modalidades de imagen. En el caso de la aplicación a microscopía de fluorescencia, los resultados de la fusión muestran un mejor contraste y nivel de detalle en comparación con cualquiera de las vistas individuales y el método no requiere de conocimiento previo acerca la función de dispersión puntual del sistema de imagen. Además, los resultados se han comparado con otros métodos existentes. Con respecto a la aplicación a imagen de resonancia magnética con realce tardío, los volúmenes fusionados resultantes pre-sentan una mejora cuantitativa en la nitidez de las estructuras relevantes y permiten una interpretación más sencilla y completa de la compleja estructura tridimensional del tejido miocárdico en pacientes con cardiopatía isquémica. Para ambas aplicaciones los resultados de esta tesis se encuentran actualmente en uso en los centros clínicos y de investigación con los que el autor ha colaborado durante este trabajo. Además se ha puesto a libre disposición de la comunidad científica la implementación del método de fusión propuesto. Por último, se ha tramitado también una solicitud de patente internacional que cubre el método de visualización desarrollado para la aplicación de Resonancia Magnética Nuclear. Abstract Nowadays three dimensional imaging techniques are common in several fields, but es-pecially in biomedical imaging, where we can find a wide range of techniques including: Laser Scanning Confocal Microscopy, Laser Scanning Two Photon Microscopy, Light Sheet Fluorescence Microscopy, Magnetic Resonance Imaging, Positron Emission To-mography, Optical Coherence Tomography, 3D Ultrasound Imaging, etc. A common denominator of all those applications being the constant need for further increasing resolution and quality of the acquired images. Interestingly, in some of the mentioned three-dimensional imaging techniques a remarkable situation arises: while a single volume does not contain enough information to represent the object being imaged within the quality parameters required by the final application, the acquisition scheme allows recording several volumes which represent different views of a given object, with each of the views providing complementary information. In this kind of situation one can get a better understanding of the object by combining several views instead of looking at each of them separately. Within such context, in this PhD Thesis we propose, develop and test new image processing methodologies based on the discrete wavelet transform for the combination, or fusion, of several views containing complementary information of a given object. The proposed fusion method exploits the scale and orientation decomposition capabil¬ities of the discrete wavelet transform to integrate in a single volume all the available information distributed among the set of acquired views. The work focuses in two different biomedical imaging modalities which provide such multi-view datasets. The first one is a particular fluorescence microscopy technique, Light-Sheet Fluorescence Microscopy, used for imaging and gaining understanding of the early development of live embryos from different animal models (like zebrafish or sea urchin). The second is Delayed Enhancement Magnetic Resonance Imaging, which is a valuable tool for assessing the viability of myocardial tissue on patients suffering from different cardiomyopathies. As part of this work, the proposed method was implemented and then validated on both imaging modalities. For the fluorescence microscopy application, the fusion results show improved contrast and detail discrimination when compared to any of the individual views and the method does not rely on prior knowledge of the system’s point spread function (PSF). Moreover, the results have shown improved performance with respect to previous PSF independent methods. With respect to its application to Delayed Enhancement Magnetic Resonance Imaging, the resulting fused volumes show a quantitative sharpness improvement and enable an easier and more complete interpretation of complex three-dimensional scar and heterogeneous tissue information in ischemic cardiomyopathy patients. In both applications, the results of this thesis are currently in use in the clinical and research centers with which the author collaborated during his work. An imple¬mentation of the fusion method has also been made freely available to the scientific community. Finally, an international patent application has been filed covering the visualization method developed for the Magnetic Resonance Imaging application.