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SpringerBriefs in Computer Science

Variational Regularization of 3D Data

Experiments with MATLAB®

Authors: Montegranario, Hebert, Espinosa, Jairo

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  • ISBN 978-1-4939-0533-1
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  • ISBN 978-1-4939-0532-4
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About this book

Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.

As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequate prerequisite.

Table of contents (8 chapters)

Table of contents (8 chapters)

Buy this book

eBook 41,64 €
price for Spain (gross)
  • ISBN 978-1-4939-0533-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 51,99 €
price for Spain (gross)
  • ISBN 978-1-4939-0532-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Variational Regularization of 3D Data
Book Subtitle
Experiments with MATLAB®
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2014
Publisher
Springer-Verlag New York
Copyright Holder
The Author(s)
eBook ISBN
978-1-4939-0533-1
DOI
10.1007/978-1-4939-0533-1
Softcover ISBN
978-1-4939-0532-4
Series ISSN
2191-5768
Edition Number
1
Number of Pages
X, 85
Number of Illustrations
21 b/w illustrations
Topics