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One of the main objectives in digital imaging is to mimic the capabilities of the human eye, and perhaps, go beyond in certain aspects. However, the human visual system is so versatile, complex, and only partially understood that no up-to-date imaging technology has been able to accurately reproduce the capabilities of the it. The extraordinary capabilities of the human eye have become a crucial shortcoming in digital imaging, since digital photography, video recording, and computer vision applications have continued to demand more realistic and accurate imaging reproduction and analytic capabilities. Over decades, researchers have tried to solve the colour constancy problem, as well as extending the dynamic range of digital imaging devices by proposing a number of algorithms and instrumentation approaches. Nevertheless, no unique solution has been identified; this is partially due to the wide range of computer vision applications that require colour constancy and high dynamic range imaging, and the complexity of the human visual system to achieve effective colour constancy and dynamic range capabilities. The aim of the research presented in this thesis is to enhance the overall image quality within an image signal processor of digital cameras by achieving colour constancy and extending dynamic range capabilities. This is achieved by developing a set of advanced image-processing algorithms that are robust to a number of practical challenges and feasible to be implemented within an image signal processor used in consumer electronics imaging devises. The experiments conducted in this research show that the proposed algorithms supersede state-of-the-art methods in the fields of dynamic range and colour constancy. Moreover, this unique set of image processing algorithms show that if they are used within an image signal processor, they enable digital camera devices to mimic the human visual system s dynamic range and colour constancy capabilities; the ultimate goal of any state-of-the-art technique, or commercial imaging device.

En imagerie couleur, un système d’acquisition capture une scène avec une haute résolution spatiale mais une résolution spectrale limitée. L’imagerie hyperspectrale permet d’acquérir la scène avec une grande résolution spectrale. Un système d’acquisition hyperspectrale est un ensemble complexe et il est difficile de l’utiliser pour acquérir des données dans une situation où les conditions d’imageries ne sont pas contrôlées. De plus, ces systèmes sont chers et souvent encombrants ou difficiles à manipuler. À cause de ces problèmes, l’utilisation de l’imagerie hyperspectrale n’a pas encore été beaucoup utilisée en vision assistée par ordinateur, et la plupart des systèmes de vision utilise l’imagerie couleur.L’imagerie multispectrale propose une solution intermédiaire, elle permet de capturer une information moins résolue selon la dimension spectrale, comparée à l’hyperspectrale, tout en préservant la résolution spatiale. Ces systèmes sont moins encombrants et moins difficiles à maitriser grâce aux récentes avancées technologiques, et arrivent sur le marché en tant que produits commerciaux. On peut citer les matrices de filtres spectraux (spectral filter arrays) qui permettent l’acquisition en temps réel d’images multispectrales grâce à l’utilisation d’unecaméra de complexité similaire à une caméra couleur. Jusqu’ici, les informations capturées par ces systèmes étaient considérées de la même manière que les imageurs hyperspectraux en champ proche, c’est à dire que pour utiliser l’information au mieux, les conditions d’acquisitions devaient être connues et le système calibré, en particulier pour l’éclairage de la scène et la dynamique de la scène.Afin d’élargir l’utilisation de l’imagerie multispectrale pour la vision par ordinateur dans des conditions générales, je propose dans cette thèse de développer les méthodes calculatoires en imagerie couleur (computational color imaging) et de les adapter aux systèmes d’imagerie multispectraux. Une caractéristique très puissante de l’imagerie couleur est de proposer un rendu constant des couleurs de la surface d’un objet à travers différentes conditions d’acquisition via l’utilisation d’algorithmes et divers traitements de l’information.Dans cette thèse, j’étends la notion de constance des couleurs et de balance des blancs de l’imagerie couleur à l’imagerie multispectrale. J’introduis le terme de constance de l’information spectrale (multispectral constancy).Je propose la construction d’un ensemble d’outils permettant la représentation constante de l’information spectrale à travers le changement d’éclairage. La validité de ces outils est évaluée à travers la reconstruction de la réflectance spectrale des objets lorsque l’éclairage change. Nous avons également acquis de nouvelles images hyperspectrales et multispectrales mises à disposition de la communauté.Ces outils et données permettront de favoriser la généralisation de l’utilisation de l’imagerie multispectrale en champ proche dans les applications classiques utilisant traditionnellement l’imagerie couleur et de sortir ce mode d’imagerie des laboratoires. L’avantage en vision par ordinateur est une meilleure analyse de la réflectance de la surface des objets et donc un avantage certain dans les tâches de classification et d’identification de matériaux. / A conventional color imaging system provides high resolution spatial information and low resolution spectral data. In contrast, a multispectral imaging system is able to provide both the spectral and spatial information of a scene in high resolution. A multispectral imaging system is complex and it is not easy to use it as a hand held device for acquisition of data in uncontrolled conditions. The use of multispectral imaging for computer vision applications has started recently but is not very efficient due to these limitations. Therefore, most of the computer vision systems still rely on traditional color imaging and the potential of multispectral imaging for these applications has yet to be explored.With the advancement in sensor technology, hand held multispectral imaging systems are coming in market. One such example is the snapshot multispectral filter array camera. So far, data acquisition from multispectral imaging systems require specific imaging conditions and their use is limited to a few applications including remote sensing and indoor systems. Knowledge of scene illumination during multispectral image acquisition is one of the important conditions. In color imaging, computational color constancy deals with this condition while the lack of such a framework for multispectral imaging is one of the major limitation in enabling the use of multispectral cameras in uncontrolled imaging environments.In this work, we extend some methods of computational color imaging and apply them to the multispectral imaging systems. A major advantage of color imaging is the ability of providing consistent color of objects and surfaces across varying imaging conditions. In this work, we extend the concept of color constancy and white balancing from color to multispectral images, and introduce the term multispectral constancy.The validity of proposed framework for consistent representation of multispectral images is demonstrated through spectral reconstruction of material surfaces from the acquired images. We have also presented a new hyperspectral reflectance images dataset in this work. The framework of multispectral constancy will make it one step closer for the use of multispectral imaging in computer vision applications, where the spectral information, as well as the spatial information of a surface will be able to provide distinctive useful features for material identification and classification tasks.

Dans cette thèse, nous étudions un phénomène optique souvent ignoré en vision par ordinateur : les inter-réflexions. Les inter-réflexions, qui peuvent être trouvées dans l’état de l’art sous le nom « illumination mutuelle », se produisent quand une surface concave est illuminée. Dans ce cas, un rayon lumineux venant de la source de lumière vers un point de la surface, va réfléchir vers d’autres points de la même surface plusieurs fois avant d’arriver à nos yeux, ou aux capteurs de l’appareil photo. Donc, un rayon inter-réfléchi entre les différents points de la surface concave, d’où le nom « inter-réflexions». Les inter-réflexions conduisent aux variations de couleurs, ou gradients de couleurs, sur la totalité de la surface concave. Ces variations sont plus au moins prononcées selon plusieurs facteurs comme la réflectance de la surface et sa géométrie. Dans ce manuscrit, nous allons montrer que ces variations de couleurs contiennent en elles des informations importantes qui méritent d’être utilisées en vision par ordinateur. Ces mêmes variations jouent un rôle important dans la perception ce qui permet à l’être humain une meilleure constance de couleur, comme montré par nos résultats empiriques. Dans l’objectif d’utiliser efficacement les inter-réflexions pour quelques applications en vision par ordinateur, nous introduisons dans ce manuscrit un modèle spectral d’inter-réflexions prenant en compte une infinité de rebonds. Ce modèle construit sur des bases radiométriques nous permet de définir la relation entre les valeurs RGB brut correspondant à la surface concave dans l’image d’un côté, et la réflectance spectrale et la géométrie de cette même surface, la distribution de puissance spectrale de l’éclairage (SPD), et les courbes des réponses spectrales de l’appareil photo de l’autre côté. Grâce à ce modèle, nous sommes capables d’étudier plusieurs applications d’inter-réflexions en estimation spectrale. Nous montrons que l’estimation de la réflectance spectrale à partir d’une seule image RGB, une tâche qui est quasi-impossible sans apprentissage même sous un éclairage connu, est devenue possible grâce aux inter-réflexions. Nos résultats ontdémontré que l’estimation de la réflectance spectrale d’une surface concave donne une précision similaire, et même parfois meilleure, en comparaison avec les approches de l’état de l’art qui ont besoin de trois images de la même surface prises sous trois différents éclairages. De plus, les inter-réflexions nous ont aidés à proposer une application plus concrète de l’estimation de la réflectance spectrale dans laquelle il est possible d’utiliser un spectre d’un éclairage standard sans nécessiter un pré-calibrage pour les paramètres de l’acquisition. Par la suite, nous démontrons que les inter-réflexions sont aussi utiles dans des applications qui utilisent des mires de couleurs, comme par exemple la caractérisation de l’appareil photo. La nature de l’inter-réflexion sur une surface d’une seule couleur conduit aux couleurs spéciales qui sont les résultats des multiplications de la réflectance spectrale avec elle-même de multiples fois. Utiliser ces couleurs avec notre modèle d’inter-réflexion aide à introduire de la non-linéarité sur les mires de couleurs et donc à obtenir une meilleure caractérisation spectrale. Par conséquent, utiliser des mires de couleurs 3D est plus bénéfique qu’ajouter des nouvelles couleurs aux mires 2D. Finalement, nous entraînons un réseau neuronal convolutif sur des images simulés d’inter-réflexions dans le but d’estimer à la fois la réflectance spectrale de la surface et la SPD de l’éclairage d’une seule image RGB. Nos résultats expérimentaux démontrent que notre approche est capable d’estimer les deux spectres avec une très bonne précision en comparaison avec les autres approches. De plus, cette approche fonctionne très bien sur les images réelles grâce aux niveaux de bruits ajoutés dans le processus d’apprentissage. / In this thesis, we study an optical phenomenon often ignored in computer vision, the interreflection phenomenon. Interreflections, which can also be found in the literature under the name mutual illumination happen whenever a concave surface is illuminated. As the name tells, a light ray coming from the light source and hitting a surface point will reflect toward some other point, then another, and so on, before reaching the camera sensor or the eye. Hence, a ray does inter-reflect between the different points of a concave surface. Interreflections lead to color variations, or color gradients, all over the concave surface. These variations are more or less pronounced depending on many factors including, but not limited to, the surface reflectance and its geometry. We will show in this manuscript that these color variations hold some important information which is worth to be used in computer vision. They also play an important role in perception leading to a better color constancy in human vision as demonstrated in our experiments. In order to be able to efficiently use interreflections in some computer vision applications, a spectral infinite-bounce model of interreflections is introduced in the manuscript. This radiometric model allows us to define the relation between the raw RGB values correspondingto the concave surface in the image on one side, and the spectral reflectance and the geometry of this surface, the spectral power distribution of the light and the spectral responses of the camera sensors on the other side. Thanks to this model, we were able to study some applications of interreflections in spectral estimation. We show that a task, such as spectral reflectance estimation form a single RGB image, which is almost impossible without learning even under known illuminant and spectral responses of the camera, is made possible thanks to interreflections. Our results show that, spectral reflectance estimation of a folded surface gives a similar accuracy and sometimes a better one when compared to the state of the art approaches that need three different images of the flat surface taken under three different illuminants. Moreover, interreflections help in proposing a more concrete application of spectral reflectance estimation where a standard light SPD can be used and no pre-calibration for the acquisition settings is needed. Later, we show that interreflections are useful in some applications which need color charts such as camera characterization. The nature of interreflections leads to special colors resulted from raising the spectral reflectance to multiple powers. Using these colors along with the interreflection model helps in introducing some non linearly-related information and thus in obtaining a better spectral characterization. Hence, using 3D color charts is more beneficial than adding new colors to 2D color charts. Finally, we train a convolutional neural network on simulated images of interreflections in order to get an estimation of both the spectral reflectance and the SPD of light from a single RGB image. The experimental results show that our approach is able to get both spectra with a very good accuracy compared to other approaches. In addition, this approach performs very well on real images thanks to the added noises in the training process.

Diss. Stockholm : Handelshögsk.

This Master’s thesis studies the possibility of using image processing as a tool to facilitate vine management, in particular shoot counting and assessment of the grapevine canopy. Both are areas where manual inspection is done today. The thesis presents methods of capturing images and segmenting different parts of a vine. It also presents and evaluates different approaches on how shoot counting can be done. Within canopy assessment, the emphasis is on methods to estimate canopy density. Other possible assessment areas are also discussed, such as canopy colour and measurement of canopy gaps and fruit exposure. An example of a vine assessment system is given.

<p>This Master’s thesis studies the possibility of using image processing as a tool to facilitate vine management, in particular shoot counting and assessment of the grapevine canopy. Both are areas where manual inspection is done today. The thesis presents methods of capturing images and segmenting different parts of a vine. It also presents and evaluates different approaches on how shoot counting can be done. Within canopy assessment, the emphasis is on methods to estimate canopy density. Other possible assessment areas are also discussed, such as canopy colour and measurement of canopy gaps and fruit exposure. An example of a vine assessment system is given.</p>

Four studies including ten experiments adresses interrelations between some major and classical issues in visual perception: 3-D perception, colour constancy, colour perception and colour vision deficiencies. The main experimental paradigm to investigate the issues is within that of simulated shape from shading. 3-D impressions are induced by projecting space-modulated illuminations onto flat surfaces (displays), varying the colours and layout of the displays and the colour and modulation of the illumination. Study I includes four experiments investigating three types of space- modulated illumination. All experiments confirmed earlier findings that chromatic colour and complex display layout with reflectance edges crossed by illumination edges enhances shape from shading. In Study II the impressions of shape from shading and real 3-D objects were compared between persons with deutan colour vision deficiencies and normals. As predicted, the deutans show fewer and less distinct 3-D impressions in situations with their specific "problem colours" red and green. They also show a generally lower tendency for 3-D impressions, interpreted as a generally weaker colour constancy. Study III presents the AMBEGUJAS phenomenon; a novel twofold ambiguous shape from shading situation, continuously alternating between two different 3-D impressions coupled with different colour attributions. One solution is of an object with two clear surface colours, the other one of an object with greyish (desaturated) colours in coloured illumination which means classical colour constancy. The phenomenon illustrates the visual processes of separating reflectance and illumination characteristics and may provide a useful experimental setting to study colour constancy. In Study IV the AMBEGUJAS phenomenon is found to be robust as to chromaticness and different luminance contrasts for both normals and deutans. However, the deutans show slower shifts between percepts and a less pronounced desaturation of colour, which indicates a weaker colour constancy. The studies add evidence to the contribution of colour to 3-D shape perception, validated in a novel way by the results on "colour-blinds". The AMBEGUJAS phenomenon provides further support that the factors affecting shape from shading and the deutans different impressions are to be understood with reference to colour constancy. The deutans different impressions compared to normals are remarkable per se, but probably with very limited implications to everyday life. / <p>Diss. (sammanfattning) Umeå : Umeå university, 1996, härtill 4 uppsatser</p> / digitalisering@umu

The visual system has evolved to deal with the consequences of our own movements onour perception. In particular, evolution has given us the ability to perceive our visual world as stableand continuous despite large shift of the image on our retinas when we move our eyes, head orbody. Animal studies have recently shown that in some cortical and sub-cortical areas involved inattention and saccade control, neurons are able to anticipate the consequences of voluntary eyemovements on their visual input. These neurons predict how the world will look like after a saccadeby remapping the location of each attended object to the place it will occupy following a saccade.In a series of studies, we first showed that remapping could be evaluated in a non-invasive fashion in human with simple apparent motion targets. Using eye movement recordingsand psychophysical methods, we evaluated the distribution of remapping errors across the visualfield and found that saccade compensation was fairly accurate. The pattern of errors observedsupport a model of space constancy based on a remapping of attention pointers and excluded otherknown models. Then using targets that moved continuously while a saccade was made across themotion path, we were able to directly visualize the remapping processes. With this novel method wedemonstrated again the existence of systematic errors of correction for the saccade, best explainedby an inaccurate remapping of expected moving target locations. We then extended our model toother body movements, and studied the contribution of sub-cortical receptors (otoliths and semi-circular canals) in the maintenance of space constancy across head movements. Contrary tostudies reporting almost perfect compensations for head movements, we observed breakdowns ofspace constancy for head tilt as well as for head translation. Then, we tested remapping of targetlocations to correct for saccades at the very edge of the visual field, remapping that would place theexpected target location outside the visual field. Our results suggest that visual areas involved inremapping construct a global representation of space extending out beyond the traditional visualfield. Finally, we conducted experiments to determine the allocation of attention across saccades.We demonstrated that the attention captured by a brief transient was remapped to the correctspatial location after the eye movement and that this shift can be observed even before thesaccade.Taken together these results demonstrate the management of attention pointers to therecovery of target locations in space as well as the ability of behavioral measurements to address atopic pioneered by eletrophysiologists.

Thesis (Ph. D.)--Miami University, Dept. of Psychology, 2007. / Title from second page of PDF document. Includes bibliographical references (p. 156-158).