Variational Methods in Imaging, Softcover reprint of hardcover 1st ed. 2009 Applied Mathematical Sciences Series, Vol. 167

This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Many numerical examples accompany the theory throughout the text. It is geared towards graduate students and researchers in applied mathematics. Researchers in the area of imaging science will also find this book appealing. It can serve as a main text in courses in image processing or as a supplemental text for courses on regularization and inverse problems at the graduate level.

Introduces variational methods with motivation from the deterministic, geometric and stochastic point of view

Presents case examples in imaging to illustrate the use of variational methods e.g. denoising, thermoacoustics, computerized tomography

Discusses link between noncovex calculus of variations, morphological analysis and level set methods

Analyses variational methods containing classical analysis of variational methods, modern analysis such as G-norm properties and nonconvex calculus of variations

Includes additional material and images online

Includes supplementary material: sn.pub/extras