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Computer Vision Analysis of Image Motion by Variational Methods (Springer Topics in Signal Processing)
Computer Vision Analysis of Image Motion by Variational Methods (Springer Topics in Signal Processing)

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...

Partial Differential Equations: Modelling and Numerical Simulation (Computational Methods in Applied Sciences)
Partial Differential Equations: Modelling and Numerical Simulation (Computational Methods in Applied Sciences)
This book is dedicated to Olivier Pironneau.

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...

Families of Conformally Covariant Differential Operators, Q-Curvature and Holography (Progress in Mathematics)
Families of Conformally Covariant Differential Operators, Q-Curvature and Holography (Progress in Mathematics)
The central object of the book is Q-curvature. This important and subtle scalar Riemannian curvature quantity was introduced by Tom Branson about 15 year ago in connection with variational formulas for determinants of conformally covariant differential operators. The book studies structural properties of Q-curvature from an extrinsic point of view...
Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)
Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques,...
Handbook of Mathematical Models in Computer Vision
Handbook of Mathematical Models in Computer Vision
David Marr's theory was a pioneering step towards understanding visual perception.
In his view human vision was based on a complete surface reconstruction
of the environment that was then used to address visual subtasks. This approach
was proven to be insufficient by neuro-biologists and complementary ideas from
statistical
...
Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)
Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)

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)'...

Introduction to Hilbert Spaces with Applications
Introduction to Hilbert Spaces with Applications
The Second Edition if this successful text offers a systematic exposition of the basic ideas and results of Hilbert space theory and functional analysis. It includes a simple introduction to the Lebesgue integral and a new chapter on wavelets. The book provides the reader with revised examples and updated diverse applications to differential and...
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications

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...

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)

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...

Super-Resolution Imaging (Digital Imaging and Computer Vision)
Super-Resolution Imaging (Digital Imaging and Computer Vision)

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...

Multiscale Theory of Composites and Random Media
Multiscale Theory of Composites and Random Media

This is the first book to introduce Green-function-based multiscale theory and the corresponding finite element method, which are readily applicable to composites and random media. The methodology is considered to be the one that most effectively tackles the uncertainty of stress propagation in complex heterogeneities of random...

Mathematical Problems in Image Processing
Mathematical Problems in Image Processing
It is surprising when we realize just how much we are surrounded by images. Images allow us not only to perform complex tasks on a daily basis, but also to communicate, transmit information, represent and understand the world around us. Just think, for instance about digital television, medical imagery, video-surveillance, etc....
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