This dissertation presents the development and use of a novel optical imaging system capable of monitoring changes in blood flow, oxygenated hemoglobin, deoxygenated hemoglobin, and absolute pO₂ in the brain. There are several imaging modalities capable of monitoring these parameters separately. Laser speckle contrast imaging (LSCI) and multi-spectral reflectance imaging (MSRI) have been used to monitor relative blood flow and hemoglobin changes respectively. Phosphorescence quenching, while not typically used for imaging, is capable of noninvasive measurements of pO₂. Combining these three techniques has led to the development of an imaging system that could ultimately lead to a better understanding of brain physiology. By combining techniques such as LSCI and MSRI, it becomes possible to estimate the cerebral metabolic rate of oxygen (CMRO₂), an important indicator of neuronal function. It is equally important to understand absolute pO₂ levels so that oxygen metabolism can be examined in context. Integrating phosphorescence quenching and a spatial light modulator into the imaging system allowed absolute pO₂ to be simultaneously measured in distinct regions. This new combined system was used to investigate pathophysiological conditions such as cortical spreading depression (CSD) and ischemia. The observed hemodynamic changes associated with these events were largely dictated by baseline oxygen levels and varied significantly in different regions. This finding highlighted the importance of having a system capable of monitoring hemodynamic changes and absolute pO₂ simultaneously while maintaining enough spatial resolution to distinguish the changes in different regions. It was found that animals with low baseline pO₂ were unable to deliver enough oxygen to the brain during events like CSD because of the high metabolic demand. In order for this technique to become more prevalent among researchers, it is essential to make it cost effective and simple to use. This was accomplished by replacing the expensive excitation sources with cheaper light emitting diodes (LEDs) and redesigning the software interface so that it was easier to control the entire device. The final system shows the potential to become a key tool for researchers studying the role of absolute pO₂ and other hemodynamic parameters during pathophysiological conditions such as CSD and ischemia. / text

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very dicult for a human op- erator to eectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identication at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the eective use of more advanced technolo- gies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identication. Before an object can be tracked, it must be detected. Motion segmentation tech- niques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erro- neous motion caused by noise and lighting eects, or due to the detection routines being unable to split occluded regions into their component objects. Particle l- ters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (of- ten manual) detection to initialise the lter. Particle lters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle lter. A novel hybrid motion segmentation / optical ow algorithm, capable of simulta- neously extracting multiple layers of foreground and optical ow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical ow is capable of extracting a mov- ing object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and signi- cant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle lter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benet from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle lter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking sys- tems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classication in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a signicant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi- automated video processing and therefore improve security in areas under surveil- lance.

L’imagerie de polarisation est une technique permettant de révéler des contrastes qui n’apparaissent pas dans les images d’intensité classiques. En d’autres termes, elle permet de transformer une différence de propriétés polarimétriques en différence de niveau de gris. Elle trouve des applications en décamouflage, télédétection, microscopie, etc. Les imageurs polarimétriques utilisent souvent des modulateurs de polarisation basés sur des matrices de cristaux liquides rapides et fiables. Cependant, les LCVR contrôlent l’état de polarisation de la lumière à seulement une longueur d’onde donnée, et si le système est utilisé à d’autres longueurs d’ondes, il a des performances réduites. Si la lumière qui illumine la scène à un spectre large, il est donc nécessaire d’insérer un filtre spectral de bande étroite dans la voie d’imagerie, ce qui a pour effet de réduire la quantité de lumière entrant dans le système et donc le rapport signal à bruit des images.Un moyen de résoudre ce problème est d’utiliser des modulateurs de polarisation achromatiques, mais cela induit un coût et une complexité accrus qui peuvent ne pas être nécessaires si l’objectif est d’améliorer la performance de détection de cible en augmentant le contraste entre l’objet d’intérêt et le fond. Dans cette thèse, j’étudie l’impact d’un élargissement du spectre d’illumination sur la performance de détection de cible par des systèmes d’imagerie polarimétriques utilisant des composants chromatiques. A travers des simulations, je montre tout d’abord qu’élargir le spectre d’illumination peut augmenter le contraste car l’augmentation du flux de lumière compense la perte de précision polarimétrique. De plus, en prenant en compte les caractéristiques polarimétriques chromatiques des composants, on peut accroître encore l’augmentation du contraste. Ces résultats sont ensuite validés à travers des expériences réelles d’imagerie polarimétrique active. Ils démontrent que la largeur du spectre d’éclairement peut être considérée comme un paramètre additionnel pour optimiser ces systèmes d’imagerie.Afin de mettre en pratique l’expertise acquise en imagerie polarimétrique active à un autre domaine, j’ai collaboré avec un partenaire industriel (Carl Zeiss, Germany) pour doter un microscope optique d’une capacité polarimétrique. L’imagerie d’un échantillon fin et transparent est un problème difficile. Par exemple, la coloration de l’échantillon peut ajouter des détails parasites et n’est pas applicable à l’imagerie du vivant. Une technique prometteuse est le contraste de phase différentiel (DPC) qui consiste à extraire le gradient de phase de l’objet à partir de deux images illuminées de manière asymétrique et acquises selon des angles complémentaires. La source de lumière est une matrice de LED programmables qui peut générer différents motifs d’illumination. Cependant, cette méthode d’imagerie prend du temps et les flashs intermittents émis par la source peuvent rendre l’observation inconfortable.J’ai donc proposé une solution alternative consistant à installer deux polariseurs avec des axes orthogonaux devant la source de lumière et une caméra sensible à la polarisation qui peut détecter simultanément des polarisations orthogonales. La lumière polarisée atteint la caméra sensible à la polarisation après avoir traversé l’échantillon transparent. Les composantes orthogonales sont extraites de l’image acquise par un procédé de débayerisation. A travers différentes expériences, je compare les performances de cette méthode innovante avec la méthode de DPC classique. Je montre qu’elles fournissent des qualités d’images similaires dans la plupart des cas alors que la nouvelle méthode permet de diviser le temps d’acquisition par deux, tout en supprimant les flashs intermittents. / Polarization imaging is a technique which reveals contrasts that do not appear in classical intensity images. It transforms the difference in polarimetric properties of a scene into difference in gray level of an image. This technique has found applications in decamouflaging, remote sensing, microscopy etc. Polarimetric imagers often use polarization modulation devices based on liquid crystal variable retarders (LCVR), which are fast and reliable. However, LCVR control the polarization state of light only at one given nominal wavelength, and performance loss might be observed if imaging is performed at other wavelengths, due to the wavelength dependence of the LCVR. If the light source that illuminates the scene has a broad spectrum, it is thus necessary to insert a narrowband spectral filter in the imaging path. However, spectral filtering significantly decreases the amount of light entering the system and thus the signal-to-noise ratio of polarimetric images.A way to circumvent this issue is to achromatize the polarization modulators. However, this comes at the price of higher complexity and cost, and this may not be needed if the objective is to improve target detection performance by increasing the target/background discriminability (or contrast). In the thesis, we present the investigation of the impact of broadening the spectrum of the light entering the system on the discriminability performance of active polarimetric systems. Through simulations, we show that broadening the bandwidth of the illumination can increase the contrast between two regions, as the increase of light flux compensates for the loss of polarimetric precision. Moreover, we show that taking into account the chromatic characteristics of the components of the imaging system, it is possible to further enhance the contrast. We validate these findings through experiments in active polarimetric imaging configuration, and demonstrate that the spectral bandwidth can be considered as an additional parameter to optimize polarimetric imaging set-ups.We collaborated with an industrial partner (Carl Zeiss, Germany) to implement polarization imaging in optical microscopy. Imaging thin and transparent specimen in microscopy is a challenging task. Staining the sample is a solution but it adds false/spurious details to the image, thus not suitable for live imaging. Recently, differential phase contrast (DPC) imaging by asymmetric illumination is proved to be a desirable choice. This works on the principle that the phase gradient of a transparent specimen can be extracted from two images, illuminated and recorded at complementary angles. Then, DPC is computed as normalized difference between two images. Here the light source is programmable LED array and different pattern of illumination can be generated. This imaging method consumes more time and intermittent flash of light from light source makes sample observation inconvenient for the observer.A practical solution we propose is to install two polarization foils with orthogonal polarization axes below the light source side by side and a polarization sensitive camera which can detect orthogonal eigen polarization states at a time in the existing setup. The polarization foils separate light waves from complementary angles since orthogonally polarized light waves do not interact with each other. The polarized light reaches polarization sensitive camera after passing through transparent sample. The pixels sensitive to horizontal and vertical polarization detect horizontal and vertical polarized light respectively. Then horizontal and vertical polarized light information are separated from the recorded image and reconstructed the missing information using debayering process. Through experiments, we show that polarization based DPC and standard DPC images have similar quality in most cases and the new technique reduces time consumption by half.

Forage quality is a principal factor in managing both herbivores and the landscapes they use. Nutrition varies across the landscape, and in turn, so do the distributions of these populations. With the rise of remote sensing technologies (i.e. satellites, unmanned aerial vehicles, and multi/hyperspectral sensors), comes the ability to index forage health and nutrition swiftly. However, no methodology has been developed which allows managers to use unmanned aerial systems to the fullest capacity. The following methodologies produce compelling evidence for predicting forage quality metrics (such as fiber, carbohydrates, and digestibility) using 5 measured bands of reflectance (Blue, Green, Red, Red Edge, and NIR), 3 derived vegetation indices (NDVI, EVI and VARI), and a variety of environmental factors (i.e. time and sun angles) in a LASSO framework. Fiber content, carbohydrates, and digestibility showed promising model performance in terms of goodness-of-fit (R2= 0.624, 0.637, and 0.639 respectively).

No description available.

This research develops a methodology for determining farm scale land managementunits (LMUs) using soil sampling data, high resolution digital multi-spectral imagery (DMSI) and a digital elevation model (DEM). The LMUs are zones within a paddock suitable for precision agriculture which are managed according to their productive capabilities. Soil sampling and analysis are crucial in depicting landscape characteristics, but costly. Data based on DMSI and DEM is available cheaply and at high resolution.The design and implementation of a two-stage methodology using a spatiallyweighted multivariate classification, for delineating LMUs is described. Utilising data on physical and chemical soil properties collected at 250 sampling locations within a 1780ha farm in Western Australia, the methodology initially classifies sampling points into LMUs based on a spatially weighted similarity matrix. The second stage delineates higher resolution LMU boundaries using DMSI and topographic variables derived from a DEM on a 10m grid across the study area. The method groups sample points and pixels with respect to their characteristics and their spatial relationships, thus forming contiguous, homogenous LMUs that can be adopted in precision agricultural applications. The methodology combines readily available and relatively cheap high resolution data sets with soil properties sampled at low resolution. This minimises cost while still forming LMUs at high resolution.The allocation of pixels to LMUs based on their DMSI and topographic variables has been verified. Yield differences between the LMUs have also been analysed. The results indicate the potential of the approach for precision agriculture and the importance of continued research in this area.

Road extraction from satellite or aerial imagery is a popular topic in remote sensing, and there are many road extraction algorithms suggested by various researches. However, the need of reliable remotely sensed road information still persists as there is no sufficiently robust road extraction algorithm yet. In this study, we explore the road extraction problem taking advantage of the multi-resolution analysis and adaptive boosting based classifiers. That is, we propose a new road extraction algorithm exploiting both spectral and structural features of the high resolution multi-spectral satellite images. The proposed model is composed of three major components / feature extraction, classification and road detection. Well-known spectral band ratios are utilized to represent reflectance properties of the data whereas a segmentation operation followed by an elongatedness scoring technique renders structural evaluation of the road parts within the multi-resolution analysis framework. The extracted features are fed into Adaptive Boosting (Adaboost) learning procedure, and the learning method iteratively combines decision trees to acquire a classifier with a high accuracy. The road network is identified from the probability map constructed by the classifier suggested by Adaboost. The algorithm is designed to be modular in the sense of its extensibility, that is / new road descriptor features can be easily integrated into the existing model. The empirical evaluation of the proposed algorithm suggests that the algorithm is capable of extracting majority of the road network, and it poses promising performance results.

Les performances des systèmes de reconnaissance des visages en utilisant des images RGB baissent rapidement quand ils sont appliqués dans des conditions d’illumination extrêmes. L’utilisation des images multispectrales représente une alternative prometteuse pour résoudre ce problème. Dans cette thèse on s’intéresse à l’utilisation des images multispectrales visibles pour la reconnaissance des visages humains. Les images multispectrales visibles sont des images capturées à des longueurs d’ondes différentes du spectre visible (band spectral) qui s’étend de 480nm à 720nm. Ces images représentent des caractéristiques qui favorisent la reconnaissance des visages humains dans des conditions particulières comme la présence d’excès d’illumination incidente sur le visage photographié. Notre travail consiste à exploiter ces caractéristiques sur des stages différentes: optimiser le choix du nombre de bandes spectrales à utiliser, optimiser les longueurs d’ondes choisies, optimiser les techniques de fusion des informations extraites à partir des différentes bandes spectrales pour avoir plus d’informations utiles et moins d’informations bruits. Plusieurs nouvelles approches ont été proposées dans le cadre de ce travail avec des résultats encourageants en termes de performances. Ces approches ont exploité plusieurs outils mathématiques pour resoudre les différents problèmes rencontrés, en particulier la formulation de la sélection des bandes spectrales optimales sous formes de problèmes d’optimisation où nous avons utilisé le « basis pursuit algorithm » pour déterminer un vecteur de poids sparse pour représenter l’importance des différentes bandes. Dans d’autres problèmes d’optimisation, nous avons attribué à chaque bande un classifieur faible, puis combiné les classifieurs faibles avec dif- férents poids associés selon l’importance. La méthode Adaboost a été utilisée pour trouver la combinaison optimale. D’autres techniques ont introduites d’une manière originale la dé- composition multilinéaire des images de visage pour formuler une sorte de base de données caractérisant les bandes spectrales. Cette base de données a été utilisée avec les nouvelles images, ou image test, pour déterminer les bandes les plus robustes contre une variation importante d’illumination. Le travail présenté dans le cadre de cette thèse est une petite contribution à la reconnaissance des visages en utilisant des images multispectrales, qui est une approche d’actualité, mais qui nécessite encore plus de développement afin de maximiser ses performances. / Face recognition systems based on ’conventional’ images have reached a significant level of maturity with some practical successes. However, their performance may degrade under poor and/or changing illumination. Multispectral imagery represents a viable alternative to conventional imaging in the search for a robust and practical identification system. Multi- spectral imaging (MI) can be defined as a ’collection of several monochrome images of the same scene, each of them taken with additional receptors sensitive to other frequencies of the visible light or to frequencies beyond the visible light like the infrared region of electro- magnetic continuum. Each image is referred to as a band or a channel. However, one weakness of MI is that they may significantly increase the system processing time because of the huge quantity of data to be mined; in some cases, hundreds of MI are taken for each subject. In this thesis, we propose to solve this problem by developing new approaches to select the set of best visible spectral bands for face matching. For this purpose, the problem of best spectral bands selection is formulated as an optimization problem where spectral bands are constrained to maximize the recognition accuracy under challenging imaging conditions. We reduce the redundancy of both spectral and spatial information without losing valuable details needed for the object recognition, discrimination and classification. We have investigated several mathematic and optimization tools widely used in the field of image processing. One of the approaches we have proposed formulated the problem of best spectral bands selection as a pursuit problem where weights of importance were affected to each spectral band and the vector of all weights was constrained to be sparse with most of its elements are zeros. In another work, we have assigned to each spectral band a linear discriminant analysis (LDA) based weak classifier. Then, all weak classifiers were boosted together using an Adaboost process. From this later, each weak classifier obtained a weight that characterizes its importance and hence the quality of the corresponding spectral band. Several other techniques were also used for best spectral bands selection including but not limited to mixture of Gaussian based modeling, multilinear sparse decomposition, image quality factors, local descriptors like SURF and HGPP, likelihood ratio and so on. These different techniques enabled to build systems for best spectral bands selection that are either static with the same bands are selected for all the subjects or dynamic with each new subject get its own set of best bands. This latter category, dynamic systems, is an original component of our work that, to the best of our knowledge, has not been proposed before; all existing systems are only static. Finally, the proposed algorithms were compared to state-of-the-art algorithms developed for face recognition purposes in general and specifically for best spectral bands selection.

L’objectif principal de ce travail est de développer des optiques moulées transparentes du visible à l’infrarouge thermique 8-12μm pour des applications de vision multi-spectrales. La recherche de compositions de verres utilisables pour ces applications a été faite parmi les verres de chalcogénures (connus pour leurs grandes transparences dans l’infrarouge), plus précisément dans les systèmes GeS2-Ga2S3-CsCl et GeSe2-Ga2Se3-CsI. Ces deux systèmes présentent des transparences étendues dans le visible avec l’ajout d’halogénures d’alcalin.En privilégiant une transparence dans le domaine visible, le système à base de soufre a été plus précisément étudié avec la sélection de deux compositions 75GeS2-15Ga2S3-10CsCl et 65GeS2-20Ga2S3-15CsCl. Les transmissions optiques, les indices de réfraction, les dispersions chromatiques et les variations d’indices en fonction de la température pour ces compositions ont été mesurés. Les propriétés thermiques, la mise en forme des verres ainsi que les propriétés mécaniques ont été présentées pour compléter la caractérisation de ces matériaux. Ces compositions possèdent de bonnes stabilités contre la cristallisation et des transparences étendues de 0,5μm à 11,5μm. Ces résultats nous permettent d’envisager la production d’optiques couvrant une large bande spectrale et de proposer une alternative au matériau ZnS pour les systèmes optiques. Cependant, les dispersions chromatiques de ces deux verres possèdent des comportements très similaires. Une étude de ce paramètre important pour corriger les aberrations chromatiques a été faite pour permettre de déterminer une composition avec une dispersion différente.Pour ces verres, l’addition de chlorure de césium engendre une légère dégradation des propriétés optiques due à la réaction du verre avec l’humidité environnante. Pour protéger ces verres contre la corrosion de l’atmosphère, une couche protectrice de ZnS a été appliquée par pulvérisation cathodique. De plus, un traitement antireflet a été appliqué par Thales Angénieux pour optimiser la transmission de ces verres dans les bandes spectrales spécifiées. Ce revêtement antireflet agit également comme un revêtement de protection. Ces travaux sur des verres à base de GeS2-Ga2S3 pour des applications optiques, nous ont également conduits à étudier ces verres contenant des ions de sodium pour la conduction ionique avec l’ajout d’halogénure de sodium (NaI et NaCl). La conductivité ionique de ces verres a été mesurée et comparée à la conductivité des verres contenant du lithium. Il a été démontré que le système GeS2-Ga2S3-NaI peut conduire à des verres avec une conductivité ionique de 10-6 S.cm-1 à température ambiante. / The objective of our study is to develop moldable optics operating simultaneously from the visible up to the thermal infrared region (8-12μm) for multispectral applications. The research of a suitable composition for optical applications has been done among chalcogenide glasses (well known for their extended transmission in the infrared domain), more precisely in the GeS2-Ga2S3-CsCl and GeSe2-Ga2Se3-CsI glass-forming systems. These two systems present extended transparency in the visible region due to alkali halide addition.In order to have enough transparency in the visible region, the sulfide based system has been more precisely studied with the selection of two compositions: 75GeS2-15Ga2S3-10CsCl and 65GeS2-20Ga2S3-15CsCl. Their optical transmissions, the refractive indices, the chromatic dispersions and the indices as function of temperature are studied. The thermal properties, molding ability and mechanical properties have been also studied in addition to the above-mentioned optical properties. These two compositions shows good stability against crystallization and extended transparency from 0,5 to 11,5 μm. It makes possible to consider the production of optics which cover a large spectral band, leading to an alternative to the ZnS for multispectral optical system. However, the chromatic dispersion of these two glasses is similar. A study of this important parameter as function of the glass composition has been performed in order to find a new composition with significantly different chromatic dispersion.For all these glasses, the addition of cesium chloride causes a slight degradation of optical properties due to its sensitivity to moisture. In order to protect these glasses against the atmospheric aggression, an efficient protective coatings of zinc sulfide has been applied by sputtering. An antireflective coating has been developed by Thales Angénieux to enhance the transmission in different specific wavelength ranges. The Antireflection coating acts also as a protective coating.This work on glasses in the GeS2- Ga2S3 system for optical applications, has also led us to study these glasses containing sodium ions for ionic conduction. The ionic conductivity has been measured and compared to that of glasses containing lithium ion. It has been demonstrated that the GeS2-Ga2S3-NaI can lead to glasses with an ionic conductivity of 10-6 S.cm-1 at room temperature.

Cette thèse porte sur l’étude des gaz et nanoparticules diélectriques de l’atmosphère, fortement incriminés pour leur rôle sur le bilan radiatif terrestre et le changement climatique.Ces travaux de recherche, réalisées au sein de l’Institut Lumière Matière, traitent plus spécifiquement de la rétrodiffusion de la lumière, résolue en polarisation, par les nanoparticules de l’atmosphère, afin d’étudier la complexité des processus atmosphériques qui la composent, tels que la nucléation. En complément à cette approche particulaire, les gazà effet de serre sont également étudiés, en suivant une méthode originale, consistant à évaluer leur concentration atmosphérique, par couplage d’un télédétecteur lidar possédant une large bande spectrale avec la spectroscopie optique de corrélation (Thomas et al., 2012, 2013a,b). Une attention particulière a été portée à la réalisation de mesures sensibles et précises utilisant un lidar multi-spectral (UV, VIS), résolu en polarisation (David et al., 2012). Comme premier résultat, un coefficient de rétrodiffusion aussi faible que (2,4 ± 0,5) × 10−8 m−1.sr−1, a été mesuré dans l’UV en polarisation croisée à celle du laser incident dans la troposphère libre, avec une limite de détection de la dépolarisation de δp = 0,6 % (proche de la dépolarisation moléculaire), observée à plus de 4 kilomètres d’altitude. Ensuite, une méthode nouvelle a été développée pour retrouver, dans un mélange externe de particules à deux/trois composantes chimiques, le coefficient de rétrodiffusion de chacune de ces composantes. Pour ce faire, le coefficient d’Angström et la dépolarisation de chaque espèce chimique doivent être déterminés précisément. On montre dans ce travail de thèse que ces coefficients peuvent être déterminés soit par simulation numérique de la diffusion simple (algorithme T-matrix), soit directement par des mesures de laboratoire. Les hypothèses et les performances de cette méthode sont ensuite discutées dans trois cas d’étude : i) mélange externe de particules desulfates avec les cendres volcaniques issues de l’éruption de 2010 du volcan Eyjafjallajökull (Miffre et al., 2011, 2012a, b) ii) mélange externe de poussières désertiques dans la troposphère libre (Miffre et al., 2011 ; Dupart et al., 2012) observé lors d’un épisode detempête de sable désertique à Lyon (juillet 2010), iii) mélange externe à trois composantes : poussières désertiques, sels de mer et particules solubles dans l’eau (David et al., 2013a). Ces mesures atmosphériques ont conduit à plusieurs résultats: (a) détermination à distance de la concentration en nombre en particules volcaniques (cas i), désertiques (cas ii) (Miffre et al.,2011). Par construction, ces mesures de concentration sont spécifiques à ces particules et intègrent les effets de taille et de sédimentation (Miffre et al., 2012b) ; (b) Evolution de la rétrodiffusion en fonction de l’hygroscopicité de ces particules ; (c) Observation de la formation de nouvelles particules dans l’atmosphère (nucléation) à partir des mesures lidar UV, résolues en polarisation. Ce résultat nouveau ouvre de nouvelles perspectives à la pointede la recherche actuellement réalisée en physico-chimie de l’atmosphère (Dupart et al., 2012). En conclusion, cette thèse explore la diffusion optique d’un ensemble de nanoparticules et l’extinction d’une nanoparticule diélectrique unique, en les mesurant de manière très sensible et précise, en atmosphère réelle comme en laboratoire, tout en étayant cette approche expérimentale par des simulations numériques. Cette approche ouvre des perspectives nouvelles, portant sur les propriétés microphysiques de ces nanoparticules atmosphériques(Dupart et al., 2012, David et al., 2013b). / Atmospheric greenhouse gases and nanometer-sized particles are incriminated for their role on the Earth radiative budget and climate. This thesis relates the research performed on thepolarization-resolved backscattering of these nano-sized particles and demonstrates itsusefulness to address complex atmospheric processes like particles nucleation. Greenhouse gases are also studied, by coupling a spectrally broadband lidar with optical correlation spectroscopy to remotely evaluate their atmospheric content (Thomas et al., 2012, 2013a,b). Special care has been taken to perform sensitive and accurate UV-VIS polarization lidar measurements (David et al., 2012). Hence, and as a first result, cross-polarized backscattering coefficients as low as (2.4 ± 0.5)×10−8 m−1.sr−1 have been measured in the troposphere, corresponding to UV-particles depolarization detection limit of 0.6 % at 4 km altitude, close to the molecular depolarization. Then, a new methodology has been developed to retrieve, in atwo/three component particle external mixture, the backscattering coefficients specific to eachparticle component (David et al., 2013a). For that purpose, accurate knowledge on the backscattering Ångstrom exponent and depolarization ratio of each particle type must beaddressed. This task is here achieved by performing either single-scattering numerical simulations using T-matrix, or alternatively by performing laboratory measurements. Thei nherent assumptions and the performance of the methodology are then discussed for three case studies of external mixing: i) spherical sulfate mixed with volcanic ash released from the Eyjafjallajökull 2010 eruption (Miffre et al., 2011, 2012a, b), ii) desert dust mixed with nondustparticles (Miffre et al., 2011 ; Dupart et al., 2012), iii) desert dust mixed with sea-salt andbackground spherical particles as an example of a three-component particle mixture (David etal., 2013a). From these field measurements, three main results have been retrieved: (a) Rangere solved particles number concentrations specific to one particle component (ash, dust)(Miffre et al., 2011, 2012b), which include the variability in the particle size distribution, the particles refractive index and possible sedimentation effects(Miffre et al., 2012b), (b) particle backscattering enhancement due to hygroscopic growth, (c) observation of new particle formation in the atmosphere using a sensitive UV polarization lidar, which is new and opens new insights at the forefront of knowledge in atmospheric physics and chemistry (Dupart etal., 2012). As a conclusion, this thesis explores the optical scattering properties of a single / an ensemble of nanoparticles, addressing them in the real atmosphere, through sensitive and accurate lidarand laboratory experiments and numerical simulations, showing new outlooks on the microphysical properties of these atmospheric nanoparticles (Dupart et al., 2012, David et al.,2013b).