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Handbook of Mathematical Methods in Imaging

  • Reference work
  • © 2015

Overview

  • Expanded and revised second edition with 10+ new entries and 200 illustrations
  • Comprehensive and rigorous treatment of mathematical methods in imaging
  • Available in both print and electronic form, with entries in hyperlinked PDF and html format
  • Includes supplementary material: sn.pub/extras

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Table of contents (44 entries)

  1. Inverse Problems – Case Examples

  2. Image Restoration and Analysis

Keywords

About this book

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.

Editors and Affiliations

  • Computational Science Center, University of Vienna, Vienna, Austria

    Otmar Scherzer

About the editor

Otmar Scherzer is a professor at the University of Austria.

Bibliographic Information

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