Compressão de Imagens Usando a Função de Peano e a Transformada Wavelet 1D

In this work, spoke about the importance of image compression for the industry, it is known that processing and image storage is always a challenge in petrobrás to optimize the storage time and store a maximum number of images and data. We present an interactive system for processing and storing images in the wavelet domain and an interface for digital image processing. The proposal is based on the Peano function and wavelet transform in 1D. The storage system aims to optimize the computational space, both for storage and for transmission of images. Being necessary to the application of the Peano function to linearize the images and the 1D wavelet transform to decompose it. These applications allow you to extract relevant information for the storage of an image with a lower computational cost and with a very small margin of error when comparing the images, original and processed, ie, there is little loss of quality when applying the processing system presented . The results obtained from the information extracted from the images are displayed in a graphical interface. It is through the graphical user interface that the user uses the files to view and analyze the results of the programs directly on the computer screen without the worry of dealing with the source code. The graphical user interface, programs for image processing via Peano Function and Wavelet Transform 1D, were developed in Java language, allowing a direct exchange of information between them and the user

Estudo comparativo da transformada Karhunen-Loève na compressão de imagens

A representação de funções através da utilização de bases (KERNEL) de representação tem sido fundamental no processamento digital de sinais. A Transformada KARHUNEN-LOÈVE (KLT), também conhecida como Transformada HOTELLING, permite a representação de funções utilizando funções-base formadas pelos autovetores da matriz de correlação do sinal considerado. Nesse aspecto essa transformada fornece uma base ótima, isto é, aquela que proporciona o menor valor de Erro Quadrático Médio entre o sinal reconstruído e o original, para um determinado número de coeficientes. A dificuldade na utilização da KLT está no tempo adicional para calcular os autovetores (base) da matriz de correlação, o que muitas vezes inviabiliza a sua utilização nas aplicações em tempo real. Em muitas aplicações a KLT é utilizada em conjunto com outras transformadas melhorando os resultados destas aplicações. Sendo considerada a transformada ótima no sentido do Erro Quadrático Médio, este trabalho apresenta um estudo da Transformada KARHUNEN-LOÈVE nas aplicações de compressão de imagens bidimensionais estáticas e em tons de cinza, realizando também a comparação desta técnica com outras técnicas (DCT e WAVELET) buscando avaliar os pontos fortes e fracos da utilização da KLT para este tipo de aplicação. Duas técnicas importantes para solucionar o problema de cálculo dos autovalores e autovetores da matriz de correlação (Método de JACOBI e Método QL) são também apresentadas neste trabalho. Os resultados são comparados utilizando a Razão Sinal/Ruído de Pico (PSNR), a Razão de Compressão (CR) e os tempos de processamento (em segundos) para geração dos arquivos compactados.

Caracterização de escoamentos turbulentos transientes usando a transformada de ondaletas

Este trabalho apresenta a aplicação da transformada de ondaletas, como ferramenta de análise para o estudo de escoamentos turbulentos transientes e não homogêneos que podem ocorrer nas situações reais de engenharia, onde fenômenos transientes e não contínuos estão normalmente presentes. O estudo experimental da turbulência em túnel de vento habitualmente pressupõe que o escoamento seja estacionário; assim, fenômenos transientes são estudados como uma sucessão de situações estacionárias intermediárias. Isto é necessário porque a ferramenta clássica para o estudo experimental da turbulência, a análise de Fourier, só se aplica a fenômenos estacionários, pois seus resultados se referem a comportamentos de conjunto e as singularidades do sinal não aparecem na análise. Para estes escoamentos onde a transformada de Fourier não se aplica ou não apresenta resultados satisfatórios, a transformada de ondaletas, entre outras possibilidades, é a ferramenta matemática que vem sendo mais freqüentemente utilizada a partir da última década. São apresentados os fundamentos matemáticos, bem como uma breve história da transformada de ondaletas, da transformada de Fourier e da estatística aplicada á turbulência. Para estudar a transformada de ondaletas e buscar a melhor forma de aplicá-la ao estudo da turbulência, foram analisados três escoamentos distintos: na esteira de um cilindro, em turbulência homogênea e em um banco de tubos de configuração quadrangular. Os resultados experimentais foram obtidos por anemometria de fio quente. As medições foram feitas em um túnel de vento, partindo do repouso até atingir o regime permanente. Os dados experimentais obtidos foram analisados utilizando técnicas de ondaletas, usando várias ondaletas e várias transformadas de ondaletas diferentes. Os resultados são comparados entre si e com a transformada de Fourier. Também foram realizados ensaios em regime permanente para várias velocidades do escoamento entre o repouso e a velocidade nominal do ventilador, com o auxílio de um inversor de freqüência. Os resultados para a variação do número de Strouhal com a velocidade, obtidos da análise destes dados pela transformada de Fourier mostraram boa concordância com os obtidos da análise de ondaletas das aquisições transientes. Os resultados mostram que a transformada de ondaletas é uma ferramenta valiosa para a análise dos dados experimentais obtidos nos problemas investigados, qualificando e complementando a análise de Fourier onde esta se aplica e substituindo-a quando o fenômeno for não estacionário.

Detecção de fusos de sono em adultos jovens por meio de transformadas wavelet

A análise do sono está baseada na polissonogra a e o sinal de EEG é o mais importante. A necessidade de desenvolver uma análise automática do sono tem dois objetivos básicos: reduzir o tempo gasto na análise visual e explorar novas medidas quantitativas e suas relações com certos tipos de distúrbios do sono. A estrutura do sinal de EEG de sono está relacionada com a chamada microestrutura do sono, que é composta por grafoelementos. Um destes grafoelementos é o fuso de sono (spindles). Foi utilizado um delineamento transversal aplicado a um grupo de indivíduos normais do sexo masculino para testar o desempenho de um conjunto de ferramentas para a detecção automática de fusos. Exploramos a detecção destes fusos de sono através de procura direta, Matching Pursuit e uma rede neural que utiliza como "input"a transformada de Gabor (GT). Em comparação com a análise visual, o método utilizando a transformada de Gabor e redes neurais apresentou uma sensibilidade de 77% e especi cidade de 73%. Já o Matching Pursuit, apesar de mais demorado, se mostrou mais e ciente, apresentando sensibilidade de 81,2% e especi cidade de 85.2%.

Reconhecimento de voz através de unidades menores do que a palavra, utilizando Wavelet Packet e SVM, em uma nova estrutura hierárquica de decisão

The automatic speech recognition by machine has been the target of researchers in the past five decades. In this period have been numerous advances, such as in the field of recognition of isolated words (commands), which has very high rates of recognition, currently. However, we are still far from developing a system that could have a performance similar to the human being (automatic continuous speech recognition). One of the great challenges of searches for continuous speech recognition is the large amount of pattern. The modern languages such as English, French, Spanish and Portuguese have approximately 500,000 words or patterns to be identified. The purpose of this study is to use smaller units than the word such as phonemes, syllables and difones units as the basis for the speech recognition, aiming to recognize any words without necessarily using them. The main goal is to reduce the restriction imposed by the excessive amount of patterns. In order to validate this proposal, the system was tested in the isolated word recognition in dependent-case. The phonemes characteristics of the Brazil s Portuguese language were used to developed the hierarchy decision system. These decisions are made through the use of neural networks SVM (Support Vector Machines). The main speech features used were obtained from the Wavelet Packet Transform. The descriptors MFCC (Mel-Frequency Cepstral Coefficient) are also used in this work. It was concluded that the method proposed in this work, showed good results in the steps of recognition of vowels, consonants (syllables) and words when compared with other existing methods in literature

Análise sísmica usando transformada de Curvelet

Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation

Momentos nulos e regularidade wavelet na detecção de falhas em sinais

Pós-graduação em Engenharia Elétrica - FEIS

Um método não-limiar para redução de ruído em sinais de voz no domínio wavelet

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise e síntese de um processador digital wavelet

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

Análise wavelet e modelo de manchas em curvas de luz estelares dos telescópios espaciais Kepler e CoRoT

Analogous to sunspots and solar photospheric faculae, which visibility is modulated by stellar rotation, stellar active regions consist of cool spots and bright faculae caused by the magnetic field of the star. Such starspots are now well established as major tracers used to estimate the stellar rotation period, but their dynamic behavior may also be used to analyze other relevant phenomena such as the presence of magnetic activity and its cycles. To calculate the stellar rotation period, identify the presence of active regions and investigate if the star exhibits or not differential rotation, we apply two methods: a wavelet analysis and a spot model. The wavelet procedure is also applied here to study pulsation in order to identify specific signatures of this particular stellar variability for different types of pulsating variable stars. The wavelet transform has been used as a powerful tool for treating several problems in astrophysics. In this work, we show that the time-frequency analysis of stellar light curves using the wavelet transform is a practical tool for identifying rotation, magnetic activity, and pulsation signatures. We present the wavelet spectral composition and multiscale variations of the time series for four classes of stars: targets dominated by magnetic activity, stars with transiting planets, those with binary transits, and pulsating stars. We applied the Morlet wavelet (6th order), which offers high time and frequency resolution. By applying the wavelet transform to the signal, we obtain the wavelet local and global power spectra. The first is interpreted as energy distribution of the signal in time-frequency space, and the second is obtained by time integration of the local map. Since the wavelet transform is a useful mathematical tool for nonstationary signals, this technique applied to Kepler and CoRoT light curves allows us to clearly identify particular signatures for different phenomena. In particular, patterns were identified for the temporal evolution of the rotation period and other periodicity due to active regions affecting these light curves. In addition, a beat-pattern vii signature in the local wavelet map of pulsating stars over the entire time span was also detected. The second method is based on starspots detection during transits of an extrasolar planet orbiting its host star. As a planet eclipses its parent star, we can detect physical phenomena on the surface of the star. If a dark spot on the disk of the star is partially or totally eclipsed, the integrated stellar luminosity will increase slightly. By analyzing the transit light curve it is possible to infer the physical properties of starspots, such as size, intensity, position and temperature. By detecting the same spot on consecutive transits, it is possible to obtain additional information such as the stellar rotation period in the planetary transit latitude, differential rotation, and magnetic activity cycles. Transit observations of CoRoT-18 and Kepler-17 were used to implement this model.

Análise wavelet da variabilidade do quasar 3C 273

Discovered in 1963, 3C 273 was the second quasar identified and cataloged in the Third Cambridge Catalog for radio sources, and the first one for which emission lines were identified with a hydrogen sequence redshifted. It is the brightest quasar of the celestial sphere, the most studied, analyzed, and with a resulting abundance of data available in a vast literature. The accurate analysis of the deviations of the spectral lines of quasars provides enough information to put in evidence the variation of fundamental constants of nature and similarly the universe expansion rate. The analysis of the variability of the light curves of these bodies, and the consequent accuracy of their periodicity, is of utmost importance as it provides an efficiency of their observations, enables a greater understanding of the physical phenomena, and makes it possible to conduct spectral observations on more accurate dates (when their light curves show pronounced peaks and therefore richer spectra information). In this master’s thesis twenty eight light curves from the quasar 3C 273 are studied, covering all the electromagnetic spectrum wavebands (radio emission to gamma rays), totaling in the analysis of four light curves for each waveband. We have applied the method of Continuous Wavelet Transform using the sixth-order (!0 = 6) Morlet wavelet function, and obtained excellent results in accordance with the literature.

Análise wavelet da variabilidade do quasar 3C 273

Discovered in 1963, 3C 273 was the second quasar identified and cataloged in the Third Cambridge Catalog for radio sources, and the first one for which emission lines were identified with a hydrogen sequence redshifted. It is the brightest quasar of the celestial sphere, the most studied, analyzed, and with a resulting abundance of data available in a vast literature. The accurate analysis of the deviations of the spectral lines of quasars provides enough information to put in evidence the variation of fundamental constants of nature and similarly the universe expansion rate. The analysis of the variability of the light curves of these bodies, and the consequent accuracy of their periodicity, is of utmost importance as it provides an efficiency of their observations, enables a greater understanding of the physical phenomena, and makes it possible to conduct spectral observations on more accurate dates (when their light curves show pronounced peaks and therefore richer spectra information). In this master’s thesis twenty eight light curves from the quasar 3C 273 are studied, covering all the electromagnetic spectrum wavebands (radio emission to gamma rays), totaling in the analysis of four light curves for each waveband. We have applied the method of Continuous Wavelet Transform using the sixth-order (!0 = 6) Morlet wavelet function, and obtained excellent results in accordance with the literature.

Análise wavelet em curvas de luz estelares de sistemas binários da missão espacial CoRoT

Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.

Análise wavelet em curvas de luz estelares de sistemas binários da missão espacial CoRoT

Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.