This dissertation addresses the problem of inferring scene depth information from a collection of calibrated images taken from different viewpoints via stereo matching. Although it has been heavily investigated for decades, depth from stereo remains a long-standing challenge and popular research topic for several reasons. First of all, in order to be of practical use for many real-time applications such as autonomous driving, accurate depth estimation in real-time is of great importance and one of the core challenges in stereo. Second, for applications such as 3D reconstruction and view synthesis, high-quality depth estimation is crucial to achieve photo realistic results. However, due to the matching ambiguities, accurate dense depth estimates are difficult to achieve. Last but not least, most stereo algorithms rely on identification of corresponding points among images and only work effectively when scenes are Lambertian. For non-Lambertian surfaces, the "brightness constancy" assumption is no longer valid. This dissertation contributes three novel stereo algorithms that are motivated by the specific requirements and limitations imposed by different applications. In addressing high speed depth estimation from images, we present a stereo algorithm that achieves high quality results while maintaining real-time performance. We introduce an adaptive aggregation step in a dynamic-programming framework. Matching costs are aggregated in the vertical direction using a computationally expensive weighting scheme based on color and distance proximity. We utilize the vector processing capability and parallelism in commodity graphics hardware to speed up this process over two orders of magnitude. In addressing high accuracy depth estimation, we present a stereo model that makes use of constraints from points with known depths - the Ground Control Points (GCPs) as referred to in stereo literature. Our formulation explicitly models the influences of GCPs in a Markov Random Field. A novel regularization prior is naturally integrated into a global inference framework in a principled way using the Bayes rule. Our probabilistic framework allows GCPs to be obtained from various modalities and provides a natural way to integrate information from various sensors. In addressing non-Lambertian reflectance, we introduce a new invariant for stereo correspondence which allows completely arbitrary scene reflectance (bidirectional reflectance distribution functions - BRDFs). This invariant can be used to formulate a rank constraint on stereo matching when the scene is observed by several lighting configurations in which only the lighting intensity varies.

We enhance photographs shot in dark environments by combining a picture taken with the available light and one taken with the flash. We preserve the ambiance of the original lighting and insert the sharpness from the flash image. We use the bilateral filter to decompose the images into detail and large scale. We reconstruct the image using the large scale of the available lighting and the detail of the flash. We detect and correct flash shadows. This combines the advantages of available illumination and flash photography. / Singapore-MIT Alliance (SMA)

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Diplomová práca je zameraná na spracovávanie obrazov sietnice s vysokým rozlíšením. Cieľom práce je zlepšiť výslednú kvalitu výsledných snímkov sietnice získaných zo sekvencie snímkov nižšej kvality. Jednotlivé snímky sú najskôr spracované pomocou bilaterálnej filtrácie a zlepšenia kontrastu. v ďalšom kroku sú odstránené rozmazané snímky a snímky zobrazujúce iné časti sietnice. Posun medzi jednotlivými snímkami v sekvencii sa odhaduje pomocou fázovej korelácie, a tieto obrazy sú potom fúzované do výsledného snímku s vysokým rozlíšením pomocou priemerovania a využitia superrozlišovacej techniky, presnejšie regularizácie pomocou bilaterálneho celkového rozptylu. Výsledné mediánové hodnoty skóre kvality získaných obrazov sú PIQUE 0.2600, NIQE 0.0701, a BRISQUE 0.3936 pre techniku priemerovania, a PIQUE 0.1063, NIQE 0.0507, and BRISQUE 0.1570 pre superrozlišovaciu techniku.

This paper concerns aliasing removal methods during the shadow displaying. Method of shadow mapping, its principles, procedure and mainly its drawbacks in the form of aliasing development are described. For the removal of this undesirable phenomenon, several aliasing suppressing methods are described - Percentage Closer Filter, Variance Shadow Map, Convulotion Shadow Map, Exponential Shadow Map a Bilateral Filter. I conclude my work with a proposal and implementation of a demonstrative application, which demonstrates the implemented results adequately. Also, the comparison of individual methods on the basis of their quality and computational demands is included.

Fyzikálně přijatelné osvětlení v reálném čase je často dosaženo použitím aproximací. Současné metody často aproximují globální osvětlení v prostoru obrazu s využitím schopností moderních grafických karet. Dva techniky z této kategorie, screen-space ambient occlusion a screen-space directional occlusion jsou popsány detailněji v této práci. Screen-space directional occlusion je zobecněná verze screen-space ambient occlusion s podporou jednoho difúzního odrazu a závislostí na směrové informaci světla. Hlavním cílem projektu bylo experimentování s těmito metodami. Pro uniformní distribuci náhodných vzorek pro obě metody byla použita Halton sekvence. Pro potlačení šumu je použita bilaterální filtrace, která bere do úvahy geometrické vlastnosti scény. Metody jsou dál zrychleny použitím nižších rozlišení pro výpočet. Rekonstrukce výsledků do původní velikosti pro vytvoření konečného obrazu je realizována pomoci joint bilateral upsamplingu. Kromě metod globálního osvětlení byly v práci použity aj metody pro mapování stínů a HDR osvětlení.

Dans cette thèse CIFRE en collaboration entre le Centre de Mathématiques et de leurs Applications, École Normale Supérieure de Cachan et l’entreprise DxO, nous abordons le problème de la décomposition additive d’une image en base et détail. Une telle décomposition est un outil fondamental du traitement d’image. Pour une application à la photographie professionnelle dans le logiciel DxO Photolab, il est nécessaire que la décomposition soit exempt d’artefact. Par exemple, dans le contexte de l’amélioration de contraste, où la base est réduite et le détail augmenté, le moindre artefact devient fortement visible. Les distorsions de l’image ainsi introduites sont inacceptables du point de vue d’un photographe.L’objectif de cette thèse est de trouver et d’étudier les filtres les plus adaptés pour effectuer cette tâche, d’améliorer les meilleurs et d’en définir de nouveaux. Cela demande une mesure rigoureuse de la qualité de la décomposition en base plus détail. Nous examinons deux artefact classiques (halo et staircasing) et en découvrons trois autres types tout autant cruciaux : les halos de contraste, le cloisonnement et les halos sombres. Cela nous conduit à construire cinq mire adaptées pour mesurer ces artefacts. Nous finissons par classer les filtres optimaux selon ces mesures, et arrivons à une décision claire sur les meilleurs filtres. Deux filtres sortent du rang, dont un proposé dans cette thèse. / In this CIFRE thesis, a collaboration between the Center of Mathematics and their Applications, École Normale Supérieure de Cachan and the company DxO, we tackle the problem of the additive decomposition of an image into base and detail. Such a decomposition is a fundamental tool in image processing. For applications to professional photo editing in DxO Photolab, a core requirement is the absence of artifacts. For instance, in the context of contrast enhancement, in which the base is reduced and the detail increased, minor artifacts becomes highly visible. The distortions thus introduced are unacceptable from the point of view of a photographer.The objective of this thesis is to single out and study the most suitable filters to perform this task, to improve the best ones and to define new ones. This requires a rigorous measure of the quality of the base plus detail decomposition. We examine two classic artifacts (halo and staircasing) and discover three more sorts that are equally crucial: contrast halo, compartmentalization, and the dark halo. This leads us to construct five adapted patterns to measure these artifacts. We end up ranking the optimal filters based on these measurements, and arrive at a clear decision about the best filters. Two filters stand out, including one we propose.