This thesis analyzes the reflectance behavior of textiles in the short-wave infrared (SWIR) band (1 – 2 microns) in order to identify/design potential diagnostic tools that allow the remote detection of human presence in a scene. Analyzing the spectral response of fabrics in the SWIR band has gained significant interest in the remote sensing community since it provides a potential path to discriminate camouflaged clothing from backgrounds that appear similar to the object of interest in the visible band. Existing research, originating primarily from the textiles community, has thoroughly documented the behavior of clothing fabrics in the visible band. Other work has shown that the differences in spectral response in the SWIR band allows for discrimination of materials that otherwise have the same visible spectral response. This work expands on those efforts in order to quantify the reflectance behavior and to better understand the physical basis for that behavior.

Described is the development of a multispectral image labeling system with emphasis on Unmanned Ground Vehicles(UGVs). UGVs operating in unstructured environments face significant problems detecting viable paths when LIDAR is the sole source for perception. Promising advances in computer vision and machine learning has shown that multispectral imagery can be effective at detecting materials in unstructured environments [1][2][3][4][5][6]. This thesis seeks to extend previous work[6][7] by performing pixel level classification with multispectral features and texture. First the images are spatially registered to create a multispectral image cube. Visual, near infrared, shortwave infrared, and visible/near infrared polarimetric data are considered. The aligned images are then used to extract features which are fed to machine learning algorithms. The class list includes common materials present in rural and urban scenes such as vehicles, standing water, various forms of vegetation, and concrete. Experiments are conducted to explore the data requirement for a desired performance and the selection of a hyper-parameter for the textural features. A complete system is demonstrated, progressing from the data collection and labeling to the analysis of the classifier performance. / Master of Science

Depuis le début des années 2000, les performances des LED ne cessent de s'améliorer et permettent l'ancrage de cette technologie dans de nombreux domaines d'applications. Stimulées par le marché de l'éclairage, les LED présentent une longue durée de vie et une grande robustesse pour un prix par watt optique défiant toute concurrence. Pour améliorer leur luminance, les LED peuvent être couplées à des concentrateurs luminescents.La première partie de cette thèse expose la mise au point des premiers concentrateurs luminescents dans SWIR (gamme 1,2-2,5 µm où les LED sont peu efficaces). Nous montrons que la luminance des concentrateurs luminescents dans le SWIR dépasse celle des LED d'un ordre de grandeur. Elle rend possible la détection de l'eau dans l'industrie agroalimentaire ainsi que l'inspection de wafers de silicium. Dans le visible, les performances des concentrateurs luminescents (luminance, spectre, prix, régime de fonctionnement) offrent une combinaison unique des avantages des lampes flash et des diodes laser. La seconde partie de cette thèse explore la possibilité d'utiliser ces concentrateurs luminescents pour pomper des lasers solides. Cette étude démontre la compatibilité de ce nouveau type de pompage avec les cristaux dopés aux métaux de transition, incontournables dans le domaine des lasers ultra-courts. Pour la première fois, un effet laser en régime relaxé est obtenu via le pompage par LED du Cr:LiSGaF, du Cr:LiSAF, de l’alexandrite, et du Ti:saphir. Ces premières démonstrations ouvrent la voie à des systèmes laser basés sur le pompage par LED. Plusieurs systèmes sont mis en place tels que des oscillateurs lasers en régime déclenché (Q-switch et cavity-dump) faisant l'objet de conversions de fréquence, et des amplificateurs d'impulsions laser. / Since the beginning of the 2000s, LED's performance have known dramatic improvements which enable this technology to settle down in numerous application areas. Driven by the lighting market, LED are characterized by their long lifetime, their ruggedness, and their low cost per emitted optical watt. In order to go beyond LED's brightness, they can be coupled to luminescent concentrators.The first part of this work exposes the development of the first luminescent concentrator in the short-wave infrared (or SWIR corresponding to the 1.2-2.5 µm band where LED have very low powers). This work shows that the brightness of the luminescent concentrators in the SWIR exceeds by one order of magnitude LED's brightness in the same spectral range. This light source allows water detection for the agrifood industry and the inspection of silicon wafers for microelectronics. In the visible, the performance of luminescent concentrators (brightness, spectrum, price, mode of operation) offer a unique trade-off between flashlamps and laser diodes. The second part of this work investigates the use luminescent concentrators emitting in the visible to pump solid-state lasers. The compatibility of this new pumping concept is attested with transition-metals-doped crystals, cornerstone of ultrafast laser sources. For the first time, laser oscillations in free-running operation are obtained by LED-pumping of Cr:LiSGAF, Cr:LiSAF, alexandrite and Ti:sapphire. These early results open the way to LED-pumped laser systems. Several systems are implemented such as laser oscillators in pulsed operation (Q-switch and cavity dump) followed by frequency conversions and laser pulses amplifiers.

The main purpose of constructing Intelligent Vehicles is to increase the safety for all traffic participants. The detection of pedestrians, as one of the most vulnerable category of road users, is paramount for any Advance Driver Assistance System (ADAS). Although this topic has been studied for almost fifty years, a perfect solution does not exist yet. This thesis focuses on several aspects regarding pedestrian classification and detection, and has the objective of exploring and comparing multiple light spectrums (Visible, ShortWave Infrared, Far Infrared) and modalities (Intensity, Depth by Stereo Vision, Motion).From the variety of images, the Far Infrared cameras (FIR), capable of measuring the temperature of the scene, are particular interesting for detecting pedestrians. These will usually have higher temperature than the surroundings. Due to the lack of suitable public datasets containing Thermal images, we have acquired and annotated a database, that we will name RIFIR, containing both Visible and Far-Infrared Images. This dataset has allowed us to compare the performance of different state of the art features in the two domains. Moreover, we have proposed a new feature adapted for FIR images, called Intensity Self Similarity (ISS). The ISS representation is based on the relative intensity similarity between different sub-blocks within a pedestrian region of interest. The experiments performed on different image sequences have showed that, in general, FIR spectrum has a better performance than the Visible domain. Nevertheless, the fusion of the two domains provides the best results. The second domain that we have studied is the Short Wave Infrared (SWIR), a light spectrum that was never used before for the task of pedestrian classification and detection. Unlike FIRcameras, SWIR cameras can image through the windshield, and thus be mounted in the vehicle's cabin. In addition, SWIR imagers can have the ability to see clear at long distances, making it suitable for vehicle applications. We have acquired and annotated a database, that we will name RISWIR, containing both Visible and SWIR images. This dataset has allowed us to compare the performance of different pedestrian classification algorithms, along with a comparison between Visible and SWIR. Our tests have showed that SWIR might be promising for ADAS applications,performing better than the Visible domain on the considered dataset. Even if FIR and SWIR have provided promising results, Visible domain is still widely used due to the low cost of the cameras. The classical monocular imagers used for object detectionand classification can lead to a computational time well beyond real-time. Stereo Vision providesa way of reducing the hypothesis search space through the use of depth information contained in the disparity map. Therefore, a robust disparity map is essential in order to have good hypothesis over the location of pedestrians. In this context, in order to compute the disparity map, we haveproposed different cost functions robust to radiometric distortions. Moreover, we have showed that some simple post-processing techniques can have a great impact over the quality of the obtained depth images.The use of the disparity map is not strictly limited to the generation of hypothesis, and couldbe used for some feature computation by providing complementary information to color images.We have studied and compared the performance of features computed from different modalities(Intensity, Depth and Flow) and in two domains (Visible and FIR). The results have showed that the most robust systems are the ones that take into consideration all three modalities, especially when dealing with occlusions.

L’intérêt principal des systèmes d’aide à la conduite (ADAS) est d’accroître la sécurité de tous les usagers de la route. Le domaine du véhicule intelligent porte une attention particulière au piéton,l’une des catégories la plus vulnérable. Bien que ce sujet ait été étudié pendant près de cinquante ans par des chercheurs, une solution parfaite n’existe pas encore. Nous avons exploré dans ce travail de thèse différents aspects de la détection et la classification du piéton. Plusieurs domaines du spectre (Visible, Infrarouge proche, Infrarouge lointain et stéréovision) ont été explorés et comparés.Parmi la multitude des systèmes imageurs existants, les capteurs infrarouge lointain (FIR),capables de capturer la température des différents objets, reste particulièrement intéressants pour la détection de piétons. Les piétons ont, le plus souvent, une température plus élevée que les autres objets. En raison du manque d’accessibilité publique aux bases de données d’images thermiques, nous avons acquis et annoté une base de donnée, nommé RIFIR, contenant à la fois des images dans le visible et dans l’infrarouge lointain. Cette base nous a permis de comparer les performances de plusieurs attributs présentés dans l’état de l’art dans les deux domaines.Nous avons proposé une méthode générant de nouvelles caractéristiques adaptées aux images FIR appelées « Intensity Self Similarity (ISS) ». Cette nouvelle représentation est basée sur la similarité relative des intensités entre différents sous-blocks dans la région d’intérêt contenant le piéton.Appliquée sur différentes bases de données, cette méthode a montré que, d’une manière générale,le spectre infrarouge donne de meilleures performances que le domaine du visible. Néanmoins, la fusion des deux domaines semble beaucoup plus intéressante.La deuxième modalité d’image à laquelle nous nous sommes intéressé est l’infrarouge très proche (SWIR, Short Wave InfraRed). Contrairement aux caméras FIR, les caméras SWIR sont capables de recevoir le signal même à travers le pare-brise d’un véhicule. Ce qui permet de les embarquer dans l’habitacle du véhicule. De plus, les imageurs SWIR ont la capacité de capturer une scène même à distance lointaine. Ce qui les rend plus appropriées aux applications liées au véhicule intelligent. Dans le cadre de cette thèse, nous avons acquis et annoté une base de données, nommé RISWIR, contenant des images dans le visible et dans le SWIR. Cette base a permis une comparaison entre différents algorithmes de détection et de classification de piétons et entre le visible et le SWIR. Nos expérimentations ont montré que les systèmes SWIR sont prometteurs pour les ADAS. Les performances de ces systèmes semblent meilleures que celles du domaine du visible.Malgré les performances des domaines FIR et SWIR, le domaine du visible reste le plus utilisé grâce à son bas coût. Les systèmes imageurs monoculaires classiques ont des difficultés à produire une détection et classification de piétons en temps réel. Pour cela, nous avons l’information profondeur (carte de disparité) obtenue par stéréovision afin de réduire l’espace d’hypothèses dans l’étape de classification. Par conséquent, une carte de disparité relativement correcte est indispensable pour mieux localiser le piéton. Dans ce contexte, une multitude de fonctions coût ont été proposées, robustes aux distorsions radiométriques, pour le calcul de la carte de disparité.La qualité de la carte de disparité, importante pour l’étape de classification, a été affinée par un post traitement approprié aux scènes routières.Les performances de différentes caractéristiques calculées pour différentes modalités (Intensité,profondeur, flot optique) et domaines (Visible et FIR) ont été étudiées. Les résultats ont montré que les systèmes les plus robustes sont ceux qui prennent en considération les trois modalités,plus particulièrement aux occultations. / The main purpose of constructing Intelligent Vehicles is to increase the safety for all traffic participants. The detection of pedestrians, as one of the most vulnerable category of road users, is paramount for any Advance Driver Assistance System (ADAS). Although this topic has been studied for almost fifty years, a perfect solution does not exist yet. This thesis focuses on several aspects regarding pedestrian classification and detection, and has the objective of exploring and comparing multiple light spectrums (Visible, ShortWave Infrared, Far Infrared) and modalities (Intensity, Depth by Stereo Vision, Motion).From the variety of images, the Far Infrared cameras (FIR), capable of measuring the temperature of the scene, are particular interesting for detecting pedestrians. These will usually have higher temperature than the surroundings. Due to the lack of suitable public datasets containing Thermal images, we have acquired and annotated a database, that we will name RIFIR, containing both Visible and Far-Infrared Images. This dataset has allowed us to compare the performance of different state of the art features in the two domains. Moreover, we have proposed a new feature adapted for FIR images, called Intensity Self Similarity (ISS). The ISS representation is based on the relative intensity similarity between different sub-blocks within a pedestrian region of interest. The experiments performed on different image sequences have showed that, in general, FIR spectrum has a better performance than the Visible domain. Nevertheless, the fusion of the two domains provides the best results. The second domain that we have studied is the Short Wave Infrared (SWIR), a light spectrum that was never used before for the task of pedestrian classification and detection. Unlike FIRcameras, SWIR cameras can image through the windshield, and thus be mounted in the vehicle’s cabin. In addition, SWIR imagers can have the ability to see clear at long distances, making it suitable for vehicle applications. We have acquired and annotated a database, that we will name RISWIR, containing both Visible and SWIR images. This dataset has allowed us to compare the performance of different pedestrian classification algorithms, along with a comparison between Visible and SWIR. Our tests have showed that SWIR might be promising for ADAS applications,performing better than the Visible domain on the considered dataset. Even if FIR and SWIR have provided promising results, Visible domain is still widely used due to the low cost of the cameras. The classical monocular imagers used for object detectionand classification can lead to a computational time well beyond real-time. Stereo Vision providesa way of reducing the hypothesis search space through the use of depth information contained in the disparity map. Therefore, a robust disparity map is essential in order to have good hypothesis over the location of pedestrians. In this context, in order to compute the disparity map, we haveproposed different cost functions robust to radiometric distortions. Moreover, we have showed that some simple post-processing techniques can have a great impact over the quality of the obtained depth images.The use of the disparity map is not strictly limited to the generation of hypothesis, and couldbe used for some feature computation by providing complementary information to color images.We have studied and compared the performance of features computed from different modalities(Intensity, Depth and Flow) and in two domains (Visible and FIR). The results have showed that the most robust systems are the ones that take into consideration all three modalities, especially when dealing with occlusions.

Massive sulfide deposits in the Noranda mining camp, northwestern Québec, are mainly associated with extensive footwall alteration defined by intense chloritization and sericitization. However, Fe-carbonate alteration also occurs in proximity to some deposits. To test the exploration significance of carbonate alteration in the camp, two areas of intense carbonate alteration were examined, around the small Delbridge deposit and near the new Pinkos occurrence in the Cyprus Rhyolite. Between 1969 and 1971, the Delbridge deposit produced 370,000 t of ore grading 9.6% Zn, 0.61% Cu, 110 g/t Ag, and 2.1 g/t Au. Recent drilling at the new Pinkos occurrence intersected 2.64 m of massive to semi-massive sulfides grading 8.1% Zn and 18.2 g/t Ag. Alteration mapping has shown that the distribution of Fe-carbonates can be used to identify vertically extensive zones of hydrothermal upflow at both properties. At Delbridge, intense Fe-carbonate alteration in brecciated rhyolite defines a pipe-like upflow zone that extends vertically for up to 300 m within the stratigraphic footwall of the massive sulfides and 100 m into the hanging wall. The location of known massive sulfide mineralization coincides with the intersection of the alteration pipe and a favorable horizon marked by the occurrence of fine-grained volcaniclastic rocks. At Pinkos, a similar zone of Fe-carbonate alteration occurs in outcrops of coherent rhyolite. Fe-carbonate alteration is most intensely developed along polygonal cooling fractures in massive rhyolite and decreases in intensity towards the centers of the columns. Fe-carbonate stringers and locally abundant matrix carbonate occur in fragmental rocks at the stratigraphic top of the coherent rhyolite flows and are most intense at the location of sulfide-bearing outcrops that mark the known mineralized horizon. Whereas Fe-carbonate alteration defines the central part of the hydrothermal upflow zones at both properties, disseminated pyrite occurs at the margins and is widespread outside the main upflow zones. This may indicate that Fe-carbonate in the main upflow zones formed at the expense of earlier disseminated sulfides. Replacement of pyrite by synvolcanic Fe-carbonate alteration at Delbridge and Pinkos can probably be attributed to a relatively high concentration of dissolved CO2, possibly of magmatic origin, in the main-stage ore-forming fluids.

Massive sulfide deposits in the Noranda mining camp, northwestern Québec, are mainly associated with extensive footwall alteration defined by intense chloritization and sericitization. However, Fe-carbonate alteration also occurs in proximity to some deposits. To test the exploration significance of carbonate alteration in the camp, two areas of intense carbonate alteration were examined, around the small Delbridge deposit and near the new Pinkos occurrence in the Cyprus Rhyolite. Between 1969 and 1971, the Delbridge deposit produced 370,000 t of ore grading 9.6% Zn, 0.61% Cu, 110 g/t Ag, and 2.1 g/t Au. Recent drilling at the new Pinkos occurrence intersected 2.64 m of massive to semi-massive sulfides grading 8.1% Zn and 18.2 g/t Ag. Alteration mapping has shown that the distribution of Fe-carbonates can be used to identify vertically extensive zones of hydrothermal upflow at both properties. At Delbridge, intense Fe-carbonate alteration in brecciated rhyolite defines a pipe-like upflow zone that extends vertically for up to 300 m within the stratigraphic footwall of the massive sulfides and 100 m into the hanging wall. The location of known massive sulfide mineralization coincides with the intersection of the alteration pipe and a favorable horizon marked by the occurrence of fine-grained volcaniclastic rocks. At Pinkos, a similar zone of Fe-carbonate alteration occurs in outcrops of coherent rhyolite. Fe-carbonate alteration is most intensely developed along polygonal cooling fractures in massive rhyolite and decreases in intensity towards the centers of the columns. Fe-carbonate stringers and locally abundant matrix carbonate occur in fragmental rocks at the stratigraphic top of the coherent rhyolite flows and are most intense at the location of sulfide-bearing outcrops that mark the known mineralized horizon. Whereas Fe-carbonate alteration defines the central part of the hydrothermal upflow zones at both properties, disseminated pyrite occurs at the margins and is widespread outside the main upflow zones. This may indicate that Fe-carbonate in the main upflow zones formed at the expense of earlier disseminated sulfides. Replacement of pyrite by synvolcanic Fe-carbonate alteration at Delbridge and Pinkos can probably be attributed to a relatively high concentration of dissolved CO2, possibly of magmatic origin, in the main-stage ore-forming fluids.

Massive sulfide deposits in the Noranda mining camp, northwestern Québec, are mainly associated with extensive footwall alteration defined by intense chloritization and sericitization. However, Fe-carbonate alteration also occurs in proximity to some deposits. To test the exploration significance of carbonate alteration in the camp, two areas of intense carbonate alteration were examined, around the small Delbridge deposit and near the new Pinkos occurrence in the Cyprus Rhyolite. Between 1969 and 1971, the Delbridge deposit produced 370,000 t of ore grading 9.6% Zn, 0.61% Cu, 110 g/t Ag, and 2.1 g/t Au. Recent drilling at the new Pinkos occurrence intersected 2.64 m of massive to semi-massive sulfides grading 8.1% Zn and 18.2 g/t Ag. Alteration mapping has shown that the distribution of Fe-carbonates can be used to identify vertically extensive zones of hydrothermal upflow at both properties. At Delbridge, intense Fe-carbonate alteration in brecciated rhyolite defines a pipe-like upflow zone that extends vertically for up to 300 m within the stratigraphic footwall of the massive sulfides and 100 m into the hanging wall. The location of known massive sulfide mineralization coincides with the intersection of the alteration pipe and a favorable horizon marked by the occurrence of fine-grained volcaniclastic rocks. At Pinkos, a similar zone of Fe-carbonate alteration occurs in outcrops of coherent rhyolite. Fe-carbonate alteration is most intensely developed along polygonal cooling fractures in massive rhyolite and decreases in intensity towards the centers of the columns. Fe-carbonate stringers and locally abundant matrix carbonate occur in fragmental rocks at the stratigraphic top of the coherent rhyolite flows and are most intense at the location of sulfide-bearing outcrops that mark the known mineralized horizon. Whereas Fe-carbonate alteration defines the central part of the hydrothermal upflow zones at both properties, disseminated pyrite occurs at the margins and is widespread outside the main upflow zones. This may indicate that Fe-carbonate in the main upflow zones formed at the expense of earlier disseminated sulfides. Replacement of pyrite by synvolcanic Fe-carbonate alteration at Delbridge and Pinkos can probably be attributed to a relatively high concentration of dissolved CO2, possibly of magmatic origin, in the main-stage ore-forming fluids.