Foundations of Computational Imaging: A Model-Based Approach

Collecting a set of classical and emerging methods not available in a single treatment, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book brings together a blend of research with applications in a variety of disciplines, including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods.

Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University. His research in computational imaging focuses on the integration of statistical signal processing, physics, and computation and on the development of applications in healthcare and for scientific, industrial, and consumer imaging products. His research resulted in the first commercial model-based iterative reconstruction system for medical X-ray computed tomography. He is co-inventor on more than 50 issued patents licensed for use in millions of consumer imaging products.