Variational Regularization of 3D Data

Name: Variational Regularization of 3D Data
SKU: 22023741
Price: 135.99 AUD
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Experiments with MATLAB®

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Paperback / softback

Series:

Springerbriefs in Computer Science

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Description

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.

Release date Australia

March 14th, 2014

Author

Audience

Professional & Vocational

Illustrations

21 Illustrations, black and white; X, 85 p. 21 illus.

Pages

Series

Springerbriefs in Computer Science

Dimensions

155x235x5

ISBN-13

9781493905324

Product ID

22023741

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