This book presents a unified view of image motion analysis under the variational framework. Variational methods, rooted in physics and mechanics, but appearing in many other domains, such as statistics, control, and computer vision, address a problem from an optimization standpoint, i.e., they formulate it as the optimization of an objective...

For more than 250 years partial differential equations have been clearly the most important tool available to mankind in order to understand a large variety of phenomena, natural at first and then those originating from human activity and technological development. Mechanics, physics and their...

A variety of problems m machine learning and digital communication deal with complex but structured natural or artificial systems. Natural patterns mat we wish to automatically classify' are a consequence of a hierarchical causal physical process. Learning about the world m which we live requires mat we extract useful sensor)'...

This book presents the most recent achievements in data assimilation in Geosciences, especially in regards to meteorology, oceanography and hydrology. It spans both theoretical and applied aspects with various methodologies including variational, Kalman filter, maximum likelihood ensemble filter and other ensemble methods. Besides data...

This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other...

This book functions as the definitive overview of the field of super-resolution imaging. Written by the leading researchers in the field of image and video super-resolution, it surveys the latest state-of-the-art techniques in super-resolution imaging. Each detailed chapter provides coverage of the implementations and applications of...