Natural scene statistics (NSS) have played an increasingly important role in both our understanding of the function and evolution of the human vision system, and in the development of modern image processing applications. Because depth/range, i.e., egocentric distance, is arguably the most important thing a visual system must compute (from an evolutionary perspective), the joint statistics between natural image and depth/range information are of particular interest. However, while there exist regular and reliable statistical models of two-dimensional (2D) natural images, there has been little work done on statistical modeling of natural luminance/chrominance and depth/disparity, and of their mutual relationships. One major reason is the dearth of high-quality three-dimensional (3D) image and depth/range database. To facilitate research progress on 3D natural scene statistics, this dissertation first presents a high-quality database of color images and accurately co-registered depth/range maps using an advanced laser range scanner mounted with a high-end digital single-lens reflex camera. By utilizing this high-resolution, high-quality database, this dissertation performs reliable and robust statistical modeling of natural image and depth/disparity information, including new bivariate and spatial oriented correlation models. In particular, these new statistical models capture higher-order dependencies embedded in spatially adjacent bandpass responses projected from natural environments, which have not yet been well understood or explored in literature. To demonstrate the efficacy and effectiveness of the advanced NSS models, this dissertation addresses two challenging, yet very important problems, depth estimation from monocular images and no-reference stereoscopic/3D (S3D) image quality assessment. A Bayesian depth estimation framework is proposed to consider the canonical depth/range patterns in natural scenes, and it forms priors and likelihoods using both univariate and bivariate NSS features. The no-reference S3D image quality index proposed in this dissertation exploits new bivariate and correlation NSS features to quantify different types of stereoscopic distortions. Experimental results show that the proposed framework and index achieve superior performance to state-of-the-art algorithms in both disciplines. / text

Cette thèse examine la relation complexe et la causalité entre la migration et le développement, sujet d'actualité vus les flux croissants de migrants et les transferts de fonds privés. La revue de la littérature théorique et empirique montre la complexité de cette relation, et l’absence de consensus dégagé par les travaux menés sur les causes et les effets de la migration sur le développement. Sur les causes de migration, une première estimation empirique montre qu’elle fait partie intégrante du processus de développement et n’est donc pas une simple conséquence de faibles niveaux de développement: le niveau de développement des pays d'origine s’accroissant, les aspirations et les capabilités des populations augmentent et si celles-ci font face à l'absence d’opportunités, elles vont migrer à condition d’en avoir les capabilités (compétences requises, moyens financiers, politiques de migration, etc.). Concernant l’impact de la migration, une deuxième estimation empirique montre un effet positif sur le développement via les transferts privés. Les modèles indiquent que leur contribution se fait à travers deux principaux canaux, l'investissement en capital et le capital humain (éducation et santé), lesquels sont susceptibles de permettre un développement à long terme des pays d'origine. Au niveau micro, une troisième série de modèles étudie le mécanisme de cet impact au niveau de ménages, à partir du cas de l'Egypte. Ces modèles confirment l'importance des transferts privés sur les niveaux d'éducation et de santé dans les ménages qui les reçoivent. Ces résultats sont censés contribuer à la compréhension de cette relation complexe entre migration et développement. / This thesis is concerned with the causal and complex relation between migration and development. A timely subject, especially with increasing flows of migrants and the remittances these migrants send home. Both the theoretical and empirical literature reviews address the complexity of this relation but consensuses on the causes and impacts of migration on development are generally inconclusive. On the causes of migration, our first empirical estimation shows that migration is part of the development process and not a simple result of its low levels: the increasing development level of the home countries increase the aspirations and capabilities of their populations and if these are faced with lack of opportunities at home, individuals seek migration provided they have the right capabilities (skills required, financial means, migration policies, etc.). On the impact of migration, our second empirical estimation gives evidence of a positive impact through remittances on the development of the home countries. The models show the positive contributions of remittances towards development through two main channels: capital investment and human capital (education and health). These two channels are believed to achieve long-term development of the home countries. At the micro level, we look at the mechanism of this impact at the household level, addressing the case study of Egypt. Our third models give evidence of the importance of these remittances in increasing both education and health status of the recipients’ households’. These findings are believed to make a contribution towards the understanding of this complex relation between migration and development.