A novel method to reduce speckle noise from a digital image is presented. Speckle noise is introduced once a coherent light source is used. In this paper, we use the Empirical Mode Decomposition(EMD) method to remove speckles caused by such kind of coherent illumination. Many filter algorithms, such as Band-pass Filter, Enhanced Frost Filter, Gamma Filter, Enhanced Lee Filter, have been extensively studied to remove the speckle. However, they cannot remove noise effectively. The EMD method is able to analysis noise efficiently. This makes it possible to accurately analyze fringes in the frequency domain and to accurately retrieve the signal.

The thesis deals with speckle suppression in images acquired by optical coherence tomograph. It is divided into four parts. The first part describes basic information about the medical imaging method. It also deals with principle of measurement. The second section discusses the formation of image speckle and selected methods to reduce them. Next part is practical and consists of data acquisition, determination of the evaluation methodology and the implementation of speckle reduction methods. The last part is focused on testing and reviews of algorithms and discussion about their results.

Los Radares de Apertura Sintética, o sistemas SAR, representan el mejorejemplo de sistemas activos de teledetección por microondas. Debido a su naturaleza coherente, un sistema SAR es capaz de adquirir información dedispersión electromagnética con una alta resolución espacial, pero por otro lado, esta naturaleza coherente provoca también la aparición de speckle.A pesar de que el speckle es una medida electromagnética, sólo puede ser analizada como una componente de ruido debido a la complejidad asociadacon el proceso de dispersión electromagnética.Para eliminar los efectos del ruido speckle adecuadamente, es necesario un modelo de ruido, capaz de identificar las fuentes de ruido y como éstasdegradan la información útil. Mientras que este modelo existe para sistemasSAR unidimensionales, conocido como modelo de ruido speckle multiplicativo,éste no existe en el caso de sistemas SAR multidimensionales.El trabajo presentado en esta tesis presenta la definición y completa validación de nuevos modelos de ruido speckle para sistemas SAR multidimensionales,junto con su aplicación para la reducción de ruido speckle y la extracción de información.En esta tesis, los datos SAR multidimensionales, se consideran bajo una formulación basada en la matriz de covarianza, ya que permite el análisisde datos sobre la base del producto complejo Hermítico de pares de imágenesSAR. Debido a que el mantenimiento de la resolución especial es un aspectoimportante del procesado de imágenes SAR, la reducción de ruido speckleestá basada, en este trabajo, en la teoría de análisis wavelet.

Many clinicians regard speckle noise as an undesirable artifact in ultrasound images masking the underlying pathology within a patient. Speckle noise is a random interference pattern formed by coherent radiation in a medium containing many sub-resolution scatterers. Speckle has a negative impact on ultrasound images as the texture does not reflect the local echogenicity of the underlying scatterers. Studies have shown that the presence of speckle noise can reduce a physician's ability to detect lesions by a factor of eight. Without speckle, small high-contrast targets, low contrast objects, and image texture can be deduced quite readily. <br /><br /> Speckle filtering of medical ultrasound images represents a critical pre-processing step, providing clinicians with enhanced diagnostic ability. Efficient speckle noise removal algorithms may also find applications in real time surgical guidance assemblies. However, it is vital that regions of interests are not compromised during speckle removal. This research pertains to the reduction of speckle noise in ultrasound images while attempting to retain clinical regions of interest. <br /><br /> Recently, the advance of wavelet theory has lead to many applications in noise reduction and compression. Upon investigation of these two divergent fields, it was found that the speckle noise tends to rotate an image's homomorphic complex-wavelet coefficients. This work proposes a new speckle reduction filter involving a counter-rotation of these complex-wavelet coefficients to mitigate the presence of speckle noise. Simulations suggest the proposed denoising technique offers superior visual quality, though its signal-to-mean-square-error ratio (S/MSE) is numerically comparable to adaptive frost and kuan filtering. <br /><br /> This research improves the quality of ultrasound medical images, leading to improved diagnosis for one of the most popular and cost effective imaging modalities used in clinical medicine.

Many clinicians regard speckle noise as an undesirable artifact in ultrasound images masking the underlying pathology within a patient. Speckle noise is a random interference pattern formed by coherent radiation in a medium containing many sub-resolution scatterers. Speckle has a negative impact on ultrasound images as the texture does not reflect the local echogenicity of the underlying scatterers. Studies have shown that the presence of speckle noise can reduce a physician's ability to detect lesions by a factor of eight. Without speckle, small high-contrast targets, low contrast objects, and image texture can be deduced quite readily. <br /><br /> Speckle filtering of medical ultrasound images represents a critical pre-processing step, providing clinicians with enhanced diagnostic ability. Efficient speckle noise removal algorithms may also find applications in real time surgical guidance assemblies. However, it is vital that regions of interests are not compromised during speckle removal. This research pertains to the reduction of speckle noise in ultrasound images while attempting to retain clinical regions of interest. <br /><br /> Recently, the advance of wavelet theory has lead to many applications in noise reduction and compression. Upon investigation of these two divergent fields, it was found that the speckle noise tends to rotate an image's homomorphic complex-wavelet coefficients. This work proposes a new speckle reduction filter involving a counter-rotation of these complex-wavelet coefficients to mitigate the presence of speckle noise. Simulations suggest the proposed denoising technique offers superior visual quality, though its signal-to-mean-square-error ratio (S/MSE) is numerically comparable to adaptive frost and kuan filtering. <br /><br /> This research improves the quality of ultrasound medical images, leading to improved diagnosis for one of the most popular and cost effective imaging modalities used in clinical medicine.

Made available in DSpace on 2014-06-12T18:02:43Z (GMT). No. of bitstreams: 2 arquivo4052_1.pdf: 1926198 bytes, checksum: a394edbf4f303fa7b25af920df83cf25 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho propõe uma técnica não-paramétrica para detecção de bordas em imagens speckle. As imagens SAR ("Synthetic aperture Radar"), sonar, B-ultrasound e laser são corrompidas por um ruído não aditivo chamado speckle. Vários modelos estatísticos foram propostos para desrever este ruído, levando ao desenvolvimento de técnicas especiais para melhoramento e análise de imagens. A distribuição G0 é um modelo estatístico que consegue descrever uma ampla gama de áreas, como, por exemplo, em dados SAR, pastos (lisos), florestas (rugosos) e áreas urbanas (muito rugosos). O objetivo deste trabalho é estudar ténicas alternativas na detecção de imagens speckled, tomando como ponto de partida Gambini et al. (2006, 2008). Um novo detector de borda baseado no teste de Kruskal Wallis é proposto. Os nossos resultados numéricos mostram que esse detector é uma alternativa atraente ao detector de M. Gambini, que é baseado na função de verossimilhançaa. Neste trabalho fornecemos evidências de que a técnica de M. Gambini pode ser substituída om sucesso pelo método Kruskal Wallis. O ganho reside em ter um algoritmo 1000 vezes mais rápido, sem omprometer a qualidade dos resultados

This thesis presents fundamental research in the field of laser vibrometry for the application to vibration measurements. A key concern for laser vibrometry is the effect of laser speckle which appears when a coherent laser beam scatters from an optically rough surface. The laser vibrometer is sensitive to changes in laser speckle which result from surface motions not in the direction of the incident beam. This adds speckle noise to the vibrometer output which can be indistinguishable from the genuine surface vibrations. This has been termed ‘pseudo-vibration' and requires careful data interpretation by the vibration engineer. This research has discovered that measurements from smooth surfaces, even when no identifiable speckle pattern is generated, can produce noise and therefore reference to speckle noise, in such circumstances, is inappropriate. This thesis has, therefore, adopted the more general term of pseudo-vibration to include noise generated from any surface roughness or treatment, i.e. including but not limited to speckle noise. This thesis develops and implements novel experimental methods to quantify pseudovibration sensitivities (transverse, tilt and rotation sensitivity) with attention focussed on commercially available laser vibrometers and consideration is given to a range of surface roughnesses and treatments. It investigates, experimentally, the fundamental behaviour of speckles and attempts to formulate, for the first time, a relationship between changes in intensity to pseudo-vibration sensitivity levels. The thesis also develops and implements models for computational simulation of pseudo-vibrations using the fundamental behaviour of speckles. The combination of experimentation and simulation improves current understanding of the pseudo-vibration mechanisms and provides the vibration engineer with a valuable resource to improve data interpretation. Two experimental methods of quantifying pseudo-vibration sensitivity are developed and successfully applied in the evaluation of transverse, tilt and rotation sensitivity for two models of commercial laser vibrometer. These evaluations cover both single beam (translational vibration measurement) and parallel beam (for angular vibration measurement) modes. The first method presented requires correction of the vibrometer measurement with an independent measurement of genuine velocity to produce an iii apparent velocity dominated by the required noise components. The second method requires a differential measurement using two vibrometers to cancel common components such as genuine velocity, leaving only uncorrelated noise from each measurement in the resulting apparent velocity. In each case, a third measurement is required of the surface motion component causing pseudo-vibration and this is used to normalise the apparent velocity. Pseudo-vibration sensitivity is then presented as a map showing the spectral shape of the noise, as a mean and standard deviation of harmonic peaks in the map and as a total rms level across a defined bandwidth. The simulations employ a novel and effective approach to modelling speckle evolution. Transverse and tilt sensitivity are predicted for the first time and are verified by the experimental study. They provide the vibration engineer with the potential to estimate pseudo-vibrations using a simple piece of software. The laser beam spot diameter has a large influence on the pseudo-vibration sensitivity. Transverse sensitivity has been quantified as around 0.03% and 0.01% (per order) of the transverse velocity of the surface for beam spot diameters of 100 μm and 600 μm respectively. Larger beam spots have been shown to significantly reduce transverse sensitivity and measurements from smoother surfaces have also shown a reduced level of transverse sensitivity. Tilt sensitivity has been quantified at about 0.1 μms-1/degs-1 and 0.3 μms-1/degs-1 (per order) of angular velocity of the surface for beam spot diameters of 100 μm and 600 μm respectively. Smaller beam spot diameters significantly reduce tilt sensitivity. The surface roughness or treatment has been shown to have little effect on the level of tilt sensitivity. Rotation sensitivity has been quantified at approximately 0.6 μms- 1/rads-1 and 1.9μms-1/rads-1 (per order) of rotation velocity of the rotor for 90 μm and 520 μm. Smaller beam spot diameters have shown a significant reduction in rotation sensitivity and measurements on smoother surfaces have shown a reduced rotation sensitivity. Focussing the laser beam approximately on the rotation axis has also shown a significant reduction in rotation sensitivity. Parallel beam rotation sensitivity has been quantified at 0.016 degs-1/rads-1 and it is demonstrated that this can adequately be estimated using the single beam rotation sensitivity.

The viability of using a slicer based integral field spectrograph (IFS) for high contrast observations has been under scrutiny due to the belief that the one dimensional coherence that persists along the slice to the point of sampling at the detector will cause the creation of secondary speckles that will not have the same characteristics as normal speckles, thus stopping us from calibrating them out. It has also been previously assumed that a suitably low differential wavefront error when moving slice to slice was not guaranteed by design. It was for these reasons that slicer based IFSs were not selected for the current generation of planet finding instruments. As part of the EPICS (Exo Planet Imaging Camera and Spectrograph for the E-ELT) design study it was decided that slicers should be re-investigated due to results from on sky observations suggesting these limitations did not exist. The purpose of this thesis was to determine whether there was validity to the concerns mentioned above and therefore to answer the question; Would implementing a slicer based integral field spectrograph limit the achievable contrast of an instrument designed for the direct detection of exoplanets? Chapter 1 gives a brief introduction into the field of exoplanet research. Charpter 2 describes the noise limiting direct detection of exoplanets and the ways to get around it. Chapter 3 gives an overview of the two types of IFS under investigation by the EPICS consortium. Chapter 4 looks into details of the EPICS instrument and the IFS design study that came about. Chapter 5 shows simulations performed for the aim of achieving better contrasts via post processing methods and accurate data reduction as well as simulations of slicer based integral field spectrographs. Experimental tests using a slicer and a preoptics setup designed to simulate the limiting noise are described in Chapter 6. Chapter 7 looks at using SINFONI for high contrast observations and Chapter 8 details the conclusions drawn from the work presented in this thesis, as well as possible extensions to it. The work performed in this thesis dispels the concerns about the continued one dimensional coherence up to the detecter and suggests that slicer based integral field spectrographs do not inherently limit the contrast achievable; Results from experiments fit well with the requirements for EPICS to achieve its goals. Simulations also supported the idea that secondary speckle noise should not be an issue for the slicer based IFS. This means that a slicer based IFS is a viable option for the EPICS instrument.

O câncer de mama é um dos maiores problemas de saúde para a população feminina, devendo ser encarado como um importante problema de saúde pública. A ultrassonografia é considerada o método mais efetivo na complementação de diagnóstico de doenças mamárias, porém a forma de aquisição desse método diagnóstico degrada a imagem sob diversas formas, destacando-se o ruído speckle, o qual deixa a imagem com aspecto granulado, dificultando assim a separabilidade entre os objetos da cena. Este trabalho apresenta uma técnica automática para segmentação de nódulos mamários em imagens de ultrassom. O algoritmo permite a extração das bordas nodulares, permitindo assim a obtenção de parâmetros clínicos utilizados no diagnóstico mamário. Todo o processo se baseia em três etapas: minimização do ruído speckle, aumento de contraste da imagem e por fim, a segmentação. A técnica utilizada para minimização do ruído speckle baseia-se na Wavelet da família Symlet; técnicas para aumento de contraste na imagem são aplicadas para a segmentação. A partir daí, é aplicado o algoritmo de segmentação Asterisco, originalmente proposto para a detecção de microcalcificações em mamografias por raios X, e que mostrou também eficiência para os objetivos deste trabalho. A técnica Asterisco em conjunto com as de pré-processamento (minimização de ruído e aumento de contraste) produziu taxa de sensibilidade na detecção de nódulos da ordem de 90%. Em relação à qualidade da segmentação, a técnica apresentada neste trabalho também se mostrou satisfatória, superior às técnicas testadas, de acordo com a análise feita pelo cálculo de coeficientes de correlação de Pearson. É possível concluir que o sistema desenvolvido neste trabalho pode constituir-se numa ferramenta eficaz de segmentação de nódulos mamários em imagens de ultrassom, auxiliando o conjunto de informações disponíveis para um classificador automático em esquemas CAD em mamografia. / Breast cancer is one of the main health problems of the female population and should be faced as an important public health care issue. The ultrasound scanning is considered the most effective in complementary method of breast diagnosis. Nevertheless, the acquisition format of this sort degrades the images in various ways, being the speckle noise of noticeably influence once it leaves the image with grainy aspect. Therefore, the separability between objects of the scene is hindered. This work presents an automatic technique of ultrasound image segmentation of breast lumps. The algorithm allows the extraction of the nodular edges permitting the clinical parameters to be obtained for the breast diagnosis. All the process is based on three steps: speckle noise minimization, image contrast intensification and finally the segmentation. The technique used on the speckle noise minimization is based on the Wavelet transform of the Symlet family; image contrast intensifications are applied for the segmentation. Thereafter the algorithm of segmentation Asterisco is applied, which is originally proposed to detect micro calcifications in X-ray mammography, and has also shown efficiency regarding the goals of the present work. The Asterisco technique along with the pre processing techniques (noise minimizing and contrast intensification) produced sensitivity rate in nodule detection by 90%. With regard to the segmentation quality, the presented technique has also proved to be satisfactory as it has superior quality to the ones tested according to the analysis made by the Pearson\'s correlation coefficients calculation. Thus, it is possible to conclude that the system, which has been developed in this work, can constitute an efficient breast lumps segmentation tool so as to aid the set of available information to an automatic classifier in mammography CAD schemes.

Before launching into ultrasound research, it is important to recall that the ultimate goal is to provide the clinician with the best possible information needed to make an accurate diagnosis. Ultrasound images are inherently affected by speckle noise, which is due to image formation under coherent waves. Thus, it appears to be sensible to reduce speckle artifacts before performing image analysis, provided that image texture that might distinguish one tissue from another is preserved. The main goal of this thesis was the development of novel speckle suppression methods from medical ultrasound images in the multiscale wavelet domain. We started by showing, through extensive modeling, that the subband decompositions of ultrasound images have significantly non-Gaussian statistics that are best described by families of heavy-tailed distributions such as the alpha-stable. Then, we developed Bayesian estimators that exploit these statistics. We used the alpha-stable model to design both the minimum absolute error (MAE) and the maximum a posteriori (MAP) estimators for alpha-stable signal mixed in Gaussian noise. The resulting noise-removal processors perform non-linear operations on the data and we relate this non-linearity to the degree of non-Gaussianity of the data. We compared our techniques to classical speckle filters and current state-of-the-art soft and hard thresholding methods applied on actual ultrasound medical images and we quantified the achieved performance improvement. Finally, we have shown that our proposed processors can find application in other areas of interest as well, and we have chosen as an illustrative example the case of synthetic aperture radar (SAR) images. / Ο απώτερος σκοπός της έρευνας που παρουσιάζεται σε αυτή τη διδακτορική διατριβή είναι η διάθεση στην κοινότητα των κλινικών επιστημόνων μεθόδων οι οποίες να παρέχουν την καλύτερη δυνατή πληροφορία για να γίνει μια σωστή ιατρική διάγνωση. Οι εικόνες υπερήχων προσβάλλονται ενδογενώς από θόρυβο, ο οποίος οφείλεται στην διαδικασία δημιουργίας των εικόνων μέσω ακτινοβολίας που χρησιμοποιεί σύμφωνες κυματομορφές. Είναι σημαντικό πριν τη διαδικασία ανάλυσης της εικόνας να γίνεται απάλειψη του θορύβου με κατάλληλο τρόπο ώστε να διατηρείται η υφή της εικόνας, η οποία βοηθά στην διάκριση ενός ιστού από έναν άλλο. Κύριος στόχος της διατριβής αυτής υπήρξε η ανάπτυξη νέων μεθόδων καταστολής του θορύβου σε ιατρικές εικόνες υπερήχων στο πεδίο του μετασχηματισμού κυματιδίων. Αρχικά αποδείξαμε μέσω εκτενών πειραμάτων μοντελοποίησης, ότι τα δεδομένα που προκύπτουν από τον διαχωρισμό των εικόνων υπερήχων σε υποπεριοχές συχνοτήτων περιγράφονται επακριβώς από μη-γκαουσιανές κατανομές βαρέων ουρών, όπως είναι οι άλφα-ευσταθείς κατανομές. Κατόπιν, αναπτύξαμε Μπεϋζιανούς εκτιμητές που αξιοποιούν αυτή τη στατιστική περιγραφή. Πιο συγκεκριμένα, χρησιμοποιήσαμε το άλφα-ευσταθές μοντέλο για να σχεδιάσουμε εκτιμητές ελάχιστου απόλυτου λάθος και μέγιστης εκ των υστέρων πιθανότητας για άλφα-ευσταθή σήματα αναμεμειγμένα με μη-γκαουσιανό θόρυβο. Οι επεξεργαστές αφαίρεσης θορύβου που προέκυψαν επενεργούν κατά μη-γραμμικό τρόπο στα δεδομένα και συσχετίζουν με βέλτιστο τρόπο αυτή την μη-γραμμικότητα με τον βαθμό κατά τον οποίο τα δεδομένα είναι μη-γκαουσιανά. Συγκρίναμε τις τεχνικές μας με κλασσικά φίλτρα καθώς και σύγχρονες μεθόδους αυστηρού και μαλακού κατωφλίου εφαρμόζοντάς τες σε πραγματικές ιατρικές εικόνες υπερήχων και ποσοτικοποιήσαμε την απόδοση που επιτεύχθηκε. Τέλος, δείξαμε ότι οι προτεινόμενοι επεξεργαστές μπορούν να βρουν εφαρμογές και σε άλλες περιοχές ενδιαφέροντος και επιλέξαμε ως ενδεικτικό παράδειγμα την περίπτωση εικόνων ραντάρ συνθετικής διατομής.