Une architecture de capteurs à pixels CMOS permettant la désertion du volume sensible par polarisation via la face avant du circuit est étudiée à travers la caractérisation en laboratoire d’un capteur prototype. Les performances de collection de charge confirment la désertion d‘une grande partie de l’épaisseur sensible. De plus, le bruit de lecture restant modeste, le capteur présente une excellente résolution en énergie pour les photons en dessous de 20 keV à des températures positives. Ces résultats soulignent l’intérêt de cette architecture pour la spectroscopie des rayons X mous et pour la trajectométrie des particules chargées en milieu très radiatif. La profondeur sur laquelle le capteur est déserté est prédite par un modèle analytique simplifié et par des calculs par éléments finis. Une méthode d’évaluation de cette profondeur par mesure indirecte est proposée. Les mesures corroborent les prédictions concernant un substrat fin, très résistif, qui est intégralement déserté et un substrat moins résistif et mesurant 40 micromètres, qui est partiellement déserté sur 18 micromètres mais détecte correctement sur la totalité de l’épaisseur. Deux développements de capteurs destinés à l’imagerie X et à la neuro-imagerie intracérébrale sur des rats éveillés et libres de leurs mouvements sont présentés. / An architecture of CMOS pixel sensor allowing the depletion of the sensitive volume through frontside biasing is studied through the characterization in laboratory of a prototype. The charge collection performances confirm the depletion of a large part of the sensitive thickness. In addition, with a modest noise level, the sensor features an excellent energy resolution for photons below 20 keV at positive temperatures. These results demonstrate that such sensors are suited for soft X-ray spectroscopy and for charged particle tracking in highly radiative environment. A simplified analytical model and finite elements calculus are used to predict the depletion depth reached. An indirect measurement method to evaluate this depth is proposed. Measurements confirm predictions for a thin highly resistive epitaxial layer, which is fully depleted, and a 40micrometers thick bulk less resistive substrate, for which depletion reached 18 micrometers but which still offers correct detection over its full depth. Two sensor designs dedicated to X-ray imaging and in-brain neuroimaging on awake and freely moving rats are presented.

The purpose of this thesis is to create an simple graphic library in the programming C language, through which it will be possible to draw and simulate the basic functions of a car backlight, and subseguently to create the graphic user interface.v The first part of the thesis is based on the study of the given issue, briefly it describes the differences between raster and vector graphics,most used formats, describes diverse color models and the area of their use, ,basic graphic adapters, video memorry and its control in the operating system Linux. In the second part there is stated the practical realization of the basic graphic algorithms needed for drawing the algorithm primitives. An mathematical aparatus described in detail and well-founded with formulas. Also there are the advantages and disatvantages of each used algorithm and their realization in the programming C language. The 3rd and the last part of the thesis is dedicated to the creation of the graphic user interface in the FreePascal programming language and further to the describtion of his main elements.

An accurate estimation of biomass burning emissions is in part limited by the lack of knowledge of fire burning phase (smoldering/flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in the night. In contrast, VIIRS 4 µm moderate resolution band #13 (M13), though capable to detect fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered due to their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to M-band pixels’ footprint that is based on DNB and M-band’s respective characteristics in their onboard schemes for detector aggregation and bow-tie effect removals. Subsequently, the visible energy fraction (VEF) as an indicator of fire burning phase is introduced and is calculated as the ratio of visible light power (VLP) and FRP for each fire pixel retrieved from VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing mostly smoldering wildfires such as peatland fires (with smaller VEF values) in Indonesia, flaming wildfires (with larger VEF values) over grasslands and savannahs in sub-Sahel region, and gas fares with largest VEF values in the Middle East. VEF is highly correlated with modified combustion efficiency (MCE) for different land cover types or regions. These results together with a case study of the 2018 California Campfire show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

En segmentation d’images, les informations de couleur et de texture sont très utilisées. Le premier apport de cette thèse se situe au niveau de l’utilisation conjointe de ces deux sources d’informations. Nous proposons alors une méthode de combinaison couleur/texture, adaptative et non paramétrique, qui consiste à combiner un (ou plus) gradient couleur et un (ou plus) gradient texture pour ensuite générer un gradient structurel utilisé comme image de potentiel dans l’algorithme de croissance de régions par LPE. L’originalité de notre méthode réside dans l’étude de la dispersion d’un nuage de point 3D dans l’espace, en utilisant une étude comparative des valeurs propres obtenues par une analyse des composantes principales de la matrice de covariance de ce nuage de points. L’approche de combinaison couleur/texture proposée est d’abord testée sur deux bases d’images, à savoir la base générique d’images couleur de BERKELEY et la base d’images de texture VISTEX. Cette thèse s’inscrivant dans le cadre des projets ViLoc (RFC) et CAPLOC (PREDIT), le deuxième apport de celle-ci se situe au niveau de la caractérisation de l’environnement de réception des signaux GNSS pour améliorer le calcul de la position d’un mobile en milieu urbain. Dans ce cadre, nous proposons d’exclure certains satellites (NLOS dont les signaux sont reçus par réflexion voir totalement bloqués par les obstacles environnants) dans le calcul de la position d’un mobile. Deux approches de caractérisation, basées sur le traitement d’images, sont alors proposées. La première approche consiste à appliquer la méthode de combinaison couleur/texture proposée sur deux bases d’images réelles acquises en mobilité, à l’aide d’une caméra fisheye installée sur le toit du véhicule de laboratoire, suivie d’une classification binaire permettant d’obtenir les deux classes d’intérêt « ciel » (signaux LOS) et « non ciel » (signaux NLOS). Afin de satisfaire la contrainte temps réel exigée par le projet CAPLOC, nous avons proposé une deuxième approche basée sur une simplification de l’image couplée à une classification pixellaire adaptée. Le principe d’exclusion des satellites NLOS permet d’améliorer la précision de la position estimée, mais uniquement lorsque les satellites LOS (dont les signaux sont reçus de manière direct) sont géométriquement bien distribués dans l’espace. Dans le but de prendre en compte cette connaissance relative à la distribution des satellites, et par conséquent, améliorer la précision de localisation, nous avons proposé une nouvelle stratégie pour l’estimation de position, basée sur l’exclusion des satellites NLOS (identifiés par le traitement d’images), conditionnée par l’information DOP, contenue dans les trames GPS. / Color and texture are two main information used in image segmentation. The first contribution of this thesis focuses on the joint use of color and texture information by developing a robust and non parametric method combining color and texture gradients. The proposed color/texture combination allows defining a structural gradient that is used as potential image in watershed algorithm. The originality of the proposed method consists in studying a 3D points cloud generated by color and texture descriptors, followed by an eigenvalue analysis. The color/texture combination method is firstly tested and compared with well known methods in the literature, using two databases (generic BERKELEY database of color images and the VISTEX database of texture images). The applied part of the thesis is within ViLoc project (funded by RFC regional council) and CAPLOC project (funded by PREDIT). In this framework, the second contribution of the thesis concerns the characterization of the environment of GNSS signals reception. In this part, we aim to improve estimated position of a mobile in urban environment by excluding NLOS satellites (for which the signal is masked or received after reflections on obstacles surrounding the antenna environment). For that, we propose two approaches to characterize the environment of GNSS signals reception using image processing. The first one consists in applying the proposed color/texture combination on images acquired in mobility with a fisheye camera located on the roof of a vehicle and oriented toward the sky. The segmentation step is followed by a binary classification to extract two classes « sky » (LOS signals) and « not sky » (NLOS signals). The second approach is proposed in order to satisfy the real-time constraint required by the application. This approach is based on image simplification and adaptive pixel classification. The NLOS satellites exclusion principle is interesting, in terms of improving precision of position, when the LOS satellites (for which the signals are received directly) are well geometrically distributed in space. To take into account the knowledge of satellite distribution and then increase the precision of position, we propose a new strategy of position estimation, based on the exclusion of NLOS satellites (identified by the image processing step), conditioned by DOP information, which is provided by GPS data.

<p>This licentiate thesis concerns the development and characterisation of X-ray imaging detector systems. “Colour” X-ray imaging opens up new perspectives within the fields of medical X-ray diagnosis and also in industrial X-ray quality control. The difference in absorption for different “colours” can be used to discern materials in the object. For instance, this information might be used to identify diseases such as brittle-bone disease. The “colour” of the X-rays can be identified if the detector system can process each X-ray photon individually. Such a detector system is called a “single photon processing” system or, less precise, a “photon counting system”.</p><p>With modern technology it is possible to construct photon counting detector systems that can resolve details to a level of approximately 50 µm. However with such small pixels a problem will occur. In a semiconductor detector each absorbed X-ray photon creates a cloud of charge which contributes to the picture achieved. For high photon energies the size of the charge cloud is comparable to 50 µm and might be distributed between several pixels in the picture. Charge sharing is a key problem since, not only is the resolution degenerated, but it also destroys the “colour” information in the picture.</p><p>The problem involving charge sharing which limits “colour” X-ray imaging is discussed in this thesis. Image quality, detector effectiveness and “colour correctness” are studied on pixellated detectors from the MEDIPIX collaboration. Characterisation measurements and simulations are compared to be able to understand the physical processes that take place in the detector. Simulations can show pointers for the future development of photon counting X-ray systems. Charge sharing can be suppressed by introducing 3D-detector structures or by developing readout systems which can correct the crosstalk between pixels.</p>

<p>Positron Emission Tomography, PET, can be used for dynamic studies in humans. In such studies a selected part of the body, often the whole brain, is imaged repeatedly after administration of a radiolabelled tracer. Such studies are performed to provide sequences of images reflecting the tracer’s kinetic behaviour, which may be related to physiological, biochemical and functional properties of tissues. This information can be obtained by analyzing the distribution and kinetic behaviour of the administered tracers in different regions, tissues and organs. Each image in the sequence thus contains part of the kinetic information about the administered tracer. </p><p>Several factors make analysis of PET images difficult, such as a high noise magnitude and correlation between image elements in conjunction with a high level of non-specific binding to the target and a sometimes small difference in target expression between pathological and healthy regions. It is therefore important to understand how these factors affect the derived quantitative measurements when using different methods such as kinetic modelling and multivariate image analysis.</p><p>In this thesis, a new method to explore the properties of the noise in dynamic PET images was introduced and implemented. The method is based on an analysis of the autocorrelation function of the images. This was followed by proposing and implementing three novel approaches for application of Principal Component Analysis, PCA, on dynamic human PET studies. The common underlying idea of these approaches was that the images need to be normalized before application of PCA to ensure that the PCA is signal driven, not noise driven. Different ways to estimate and correct for the noise variance were investigated. Normalizations were carried out Slice-Wise (SW), for the whole volume at once, and in both image domain and sinogram domain respectively. We also investigated the value of masking out and removing the area outside the brain for the analysis. </p><p>The results were very encouraging. We could demonstrate that for phantoms as well as for real image data, the applied normalizations allow PCA to reveal the signal much more clearly than what can be seen in the original image data sets. Using our normalizations, PCA can thus be used as a multivariate analysis technique that without any modelling assumptions can separate important kinetic information into different component images. Furthermore, these images contained optimized signal to noise ratio (SNR), low levels of noise and thus showed improved quality and contrast. This should allow more accurate visualization and better precision in the discrimination between pathological and healthy regions. Hopefully this can in turn lead to improved clinical diagnosis. </p>

This thesis, Earth satellites and detection of air andground based activities by Ulf Ekblad of the Physics departmentat the Royal Institute of Technology (KTH), addresses theproblem of detecting military activities in imagery. Examplesof various techniques are presented. In particular, problemsassociated with "novelties" and "changes" in an image arediscussed and various algorithms presented. The imagery usedincludes satellite imagery, aircraft imagery, and photos offlying aircraft. The timely delivery of satellite imagery is limited by thelaws of celestial mechanics. This and other information aspectsof imagery are treated. It is e.g. shown that dozens ofsatellites may be needed if daily observations of a specificsite on Earth are to be conducted from low Earth orbit. New findings from bioinformatics and studies of small mammalvisual systems are used. The Intersecting Cortical Model (ICM),which is a reduced variant of the Pulse-Coupled Neural Network(PCNN), is used on various problems among which are changedetection. Still much more could be learnt from biologicalsystems with respect to pre- and post-processing as well asintermediate processing stages. Simulated satellite imagery is used for determining theresolution limit for detection of tanks. The necessary pixelsize is shown to be around 6 m under the conditions of thissimulation. Difference techniques are also tested on Landsat satelliteimagery with the purpose of detecting underground nuclearexplosions. In particular, it is shown that this can easily bedone with 30 m resolution images, at least in the case studied.Satellite imagery from SPOT is used for detecting undergroundnuclear explosions prior to the detonations, i.e. under certainconditions 10 m resolution images can be used to detectpreparations of underground nuclear explosions. This type ofinformation is important for ensuring the compliance of nucleartest ban treaties. Furthermore, the necessity for havingcomplementary information in order to be able to interpretimages is also shown. Keywords: Remote sensing, reconnaissance, sensor,information acquisition, satellite imagery, image processing,image analysis, change detection, pixel difference, neuronnetwork, cortex model, PCNN, ICM, entanglement, Earthobservation, nuclear explosion, SPOT, Landsat, verification,orbit.

Positron Emission Tomography, PET, can be used for dynamic studies in humans. In such studies a selected part of the body, often the whole brain, is imaged repeatedly after administration of a radiolabelled tracer. Such studies are performed to provide sequences of images reflecting the tracer’s kinetic behaviour, which may be related to physiological, biochemical and functional properties of tissues. This information can be obtained by analyzing the distribution and kinetic behaviour of the administered tracers in different regions, tissues and organs. Each image in the sequence thus contains part of the kinetic information about the administered tracer. Several factors make analysis of PET images difficult, such as a high noise magnitude and correlation between image elements in conjunction with a high level of non-specific binding to the target and a sometimes small difference in target expression between pathological and healthy regions. It is therefore important to understand how these factors affect the derived quantitative measurements when using different methods such as kinetic modelling and multivariate image analysis. In this thesis, a new method to explore the properties of the noise in dynamic PET images was introduced and implemented. The method is based on an analysis of the autocorrelation function of the images. This was followed by proposing and implementing three novel approaches for application of Principal Component Analysis, PCA, on dynamic human PET studies. The common underlying idea of these approaches was that the images need to be normalized before application of PCA to ensure that the PCA is signal driven, not noise driven. Different ways to estimate and correct for the noise variance were investigated. Normalizations were carried out Slice-Wise (SW), for the whole volume at once, and in both image domain and sinogram domain respectively. We also investigated the value of masking out and removing the area outside the brain for the analysis. The results were very encouraging. We could demonstrate that for phantoms as well as for real image data, the applied normalizations allow PCA to reveal the signal much more clearly than what can be seen in the original image data sets. Using our normalizations, PCA can thus be used as a multivariate analysis technique that without any modelling assumptions can separate important kinetic information into different component images. Furthermore, these images contained optimized signal to noise ratio (SNR), low levels of noise and thus showed improved quality and contrast. This should allow more accurate visualization and better precision in the discrimination between pathological and healthy regions. Hopefully this can in turn lead to improved clinical diagnosis.

This work extends the technology of amorphous silicon (a-Si) thin film transistors (TFTs) from traditional switching applications to on-pixel signal amplification for large area digital imaging and in particular, is aimed towards enabling emerging low noise, high resolution and high frame rate medical diagnostic imaging modalities such as digital tomosynthesis. A two transistor (2T) pixel amplifier circuit based on a novel charge-gate thin film transistor (TFT) device architecture is introduced to shrink the TFT based pixel readout circuit size and complexity and thus, improve the imaging array resolution and reliability of the TFT fabrication process. The high resolution pixel amplifier results in improved electrical performance such as on-pixel amplification gain, input referred noise and faster readouts. In this research, a charge-gated TFT that operates as both a switched amplifier and driver is used to replace two transistors (the addressing switch and the amplifier transistor) of previously reported three transistor (3T) APS pixel circuits.. In addition to enabling smaller pixels, the proposed 2T pixel amplifier results in better signal-to-noise (SNR) by removing the large flicker noise source associated with the switched TFT and increased pixel transconductance gain since the large ON-state resistance of the switched TFT is removed from the source of the amplifier TFT. Alternate configurations of 2T APS architectures based on source or drain switched TFTs are also investigated, compared, and contrasted to the gate switched architecture using charge-gated TFT. A new driving scheme based on multiple row resetting is introduced which combined with the on-pixel gain of the APS, offers considerable improvements in imaging frame rates beyond those feasible for PPS based pixels. The novel developed 2T APS architectures is implemented in single pixel test structures and in 88 pixel test arrays with a pixel pitch of 100 µm. The devices were fabricated using an in-house developed top-gate TFT fabrication process. Measured characteristics of the test devices confirm the performance expectations of the 2T architecture design. Based on parameters extracted from fabricated TFTs, the input referred noise is calculated, and the instability in pixel transconductance gain over prolonged operation tine is projected for different imaging frame rates. 2T APS test arrays were packaged and integrated with an amorphous selenium (a-Se) direct x-ray detector, and the x-ray response of the a-Se detector integrated with the novel readout circuit was evaluated. The special features of the APS such as non-destructive readout and voltage programmable on-pixel gain control are verified. The research presented in this thesis extends amorphous silicon pixel amplifier technology into the area of high density pixel arrays such as large area medical X-ray imagers for digital mammography tomosynthesis. It underscores novel device and circuit design as an effective method of overcoming the inherent shortcomings of the a-Si material . Although the developed device and circuit ideas were implemented and tested using a-Si TFTs, the scope of the device and circuit designs is not limited to amorphous silicon technology and has the potential to be applied to more mainstream technologies, for example, in CMOS active pixel sensor (APS) based digital cameras.

This work extends the technology of amorphous silicon (a-Si) thin film transistors (TFTs) from traditional switching applications to on-pixel signal amplification for large area digital imaging and in particular, is aimed towards enabling emerging low noise, high resolution and high frame rate medical diagnostic imaging modalities such as digital tomosynthesis. A two transistor (2T) pixel amplifier circuit based on a novel charge-gate thin film transistor (TFT) device architecture is introduced to shrink the TFT based pixel readout circuit size and complexity and thus, improve the imaging array resolution and reliability of the TFT fabrication process. The high resolution pixel amplifier results in improved electrical performance such as on-pixel amplification gain, input referred noise and faster readouts. In this research, a charge-gated TFT that operates as both a switched amplifier and driver is used to replace two transistors (the addressing switch and the amplifier transistor) of previously reported three transistor (3T) APS pixel circuits.. In addition to enabling smaller pixels, the proposed 2T pixel amplifier results in better signal-to-noise (SNR) by removing the large flicker noise source associated with the switched TFT and increased pixel transconductance gain since the large ON-state resistance of the switched TFT is removed from the source of the amplifier TFT. Alternate configurations of 2T APS architectures based on source or drain switched TFTs are also investigated, compared, and contrasted to the gate switched architecture using charge-gated TFT. A new driving scheme based on multiple row resetting is introduced which combined with the on-pixel gain of the APS, offers considerable improvements in imaging frame rates beyond those feasible for PPS based pixels. The novel developed 2T APS architectures is implemented in single pixel test structures and in 88 pixel test arrays with a pixel pitch of 100 µm. The devices were fabricated using an in-house developed top-gate TFT fabrication process. Measured characteristics of the test devices confirm the performance expectations of the 2T architecture design. Based on parameters extracted from fabricated TFTs, the input referred noise is calculated, and the instability in pixel transconductance gain over prolonged operation tine is projected for different imaging frame rates. 2T APS test arrays were packaged and integrated with an amorphous selenium (a-Se) direct x-ray detector, and the x-ray response of the a-Se detector integrated with the novel readout circuit was evaluated. The special features of the APS such as non-destructive readout and voltage programmable on-pixel gain control are verified. The research presented in this thesis extends amorphous silicon pixel amplifier technology into the area of high density pixel arrays such as large area medical X-ray imagers for digital mammography tomosynthesis. It underscores novel device and circuit design as an effective method of overcoming the inherent shortcomings of the a-Si material . Although the developed device and circuit ideas were implemented and tested using a-Si TFTs, the scope of the device and circuit designs is not limited to amorphous silicon technology and has the potential to be applied to more mainstream technologies, for example, in CMOS active pixel sensor (APS) based digital cameras.