Gerhard Winkler Livres

Focusing on a probabilistic approach, this text explores Bayesian Image Analysis, a framework established by notable researchers. It emphasizes the significance of prior models and discrete Markov random fields, contrasting with traditional ad hoc methods. The book addresses various imaging challenges, including restoration, edge detection, and motion analysis, while hinting at future advancements in object recognition. Supported by compelling experiments, it highlights the rapid evolution of this field, making it a vital resource for understanding modern image analysis techniques.

"This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used....This book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor…he doesn’t neglect applications, providing numerous examples of applications to illustrate the theory." -- MATHEMATICAL REVIEWS