Handbook of Mathematical Methods in Imaging

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The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous.

This expanded and revised second edition contains updates to existing chapters and 16 additional entries on important mathematical methods such as graph cuts, morphology, discrete geometry, PDEs, conformal methods, to name a few. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 200 illustrations and an extended bibliography.

It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Author(s): Otmar Scherzer (eds.)
Series: Springer Reference
Edition: 2
Publisher: Springer-Verlag New York
Year: 2015

Language: English
Pages: 2178
Tags: Mathematical Applications in Computer Science; Image Processing and Computer Vision; Signal, Image and Speech Processing; Numerical Analysis; Imaging / Radiology

Front Matter....Pages i-xviii
Front Matter....Pages 1-1
Front Matter....Pages 3-46
Front Matter....Pages 47-90
Front Matter....Pages 91-123
Front Matter....Pages 125-155
Back Matter....Pages 157-204
....Pages 205-256