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C. 3. Théorie, . Transport, and . La, 3 Théorie du Transport de la Lumière La simulation du transport de la lumière nécessite de définir une description de la lumière ainsi que de son interaction avec la matière Un modèle du transport de la lumière définit ces éléments. Dans ce chapitre, nous décrivons de façon concise différents modèles à notre disposition (Section 2.1) dont celui utilisé majoritairement en rendu basé sur la physique: l'Optique géométrique. Puis, à partir de la définition intégrale du transport de la lumière, nous étudierons les méthodes d'intégration à base de light-paths (Chapter

C. 4. Analysis, . Du, and . De-la-lumière-c, 4 Analysis Fréquentielle du Transport de la Lumière Dans les chapitres précédents, nous avons montré le besoin d'une analyse

C. Figure, 4 ? Nous voulons exprimer la variation de la fonction de radiance L pour de petites variations de ces paramètres noté l. Pour cela, nous avons besoin de définir la variation locale de l, dl et d

. Dans-le-chapitre and . La-réflection, Dans ce chapitre, nous présentons des outils pour évaluer des informations sur le spectrum du light-field local après une chaine d'opérateurs. L'évaluation du spectre complet n'est pas possible dans notre contexte, c'est pourquoi nous utilisons des descripteurs. L'étendue spatiale et l'orientation du spectre sont des informations d'intérêt car elles permettent de savoir quel point le signal varie et dans quelle direction. L'évaluation du spectrum de l'occclusion est aussi impossible dans notre contexte. Nous avons montré dans le précédent chapitre qu'il était possible d'estimer un specte approché à partir de la distance à l'object ainsi qu'a partir de sa profondeur et direction, Nous proposons une méthode basée sur un grille de voxels pour évaluer ces quantités. Dans ce chapitre, nous présentons le contributions suivantes

C. 6. Applications-de-l-'analyse, . Fréquentielle, . Transport, and . La, 6 Applications de l'Analyse Fréquentielle du Transport de la Lumière Nous avons montré comment dériver le contenu fréquentiel local aux alentours d'un light-path en utilisant un ensemble d'opérateurs définis sur des fonctions de radiance 5D (Chapter 3) Nous avons adapté cette analyse en un ensemble d'opérations sur une représentation générique, la matrice de covariance (Chapter 4) Dans ce chapitre, nous présentons les applications de la matrice de covariance. Nous montrons son utilité pour les algorithmes de Monte Carlo ou les algorithmes d'estimation de densité et prouvons qu'elle est efficace pour un bon nombre d'effets lumineux comme le depth-of-field, le motion blur ou les mileux participants, nous présentons les contributions suivantes