Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

The rapid development of new imaging hardware, the advance in medical imaging, the advent of multi-sensor data fusion and multimodal imaging, as well as the advances in computer vision have sparked numerous research endeavours leading to highly sophisticated and rigorous mathematical models and theories. Motivated
by the increasing use of variational models, shapes and flows, differential geometry, optimisation theory, numerical analysis, statistical/Bayesian graphical models, machine learning, and deep learning, we have invited contributions from leading researchers and publish this handbook to review and capture the state of the art of
research in Computer Vision and Imaging.
This constantly improving technology that generates new demands not readily met by existing mathematical concepts and algorithms provides a compelling justification for such a book to meet the ever-growing challenges in applications and to drive future development. As a consequence, new mathematical models
have to be found, analysed and realised in practice. Knowing the precise state-of-the-art developments is key, and hence this book will serve the large community of mathematics, imaging, computer vision, computer sciences, statistics, and, in general, imaging and vision research.
Our primary audience are• Graduate students
• Researchers
• Imaging and vision practitioners
• Applied mathematicians
• Medical imagers
• Engineers
• Computer scientists