Variational Regularization of 3D Data

Experiments with MATLAB®

Hebert Montegranario, Jairo Espinosa (Autoren)

Buch | Softcover

85 Seiten

2014
Springer-Verlag New York Inc.
978-1-4939-0532-4 (ISBN)

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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.

3D Data in Computer vision and technology.- Function Spaces and Reconstruction.- Variational methods.- Interpolation: From one to several variables.- Functionals and their physical interpretations.- Regularization and inverse theory.- 3D Interpolation and approximation.- Radial basis functions.

Reihe/Serie	SpringerBriefs in Computer Science
Zusatzinfo	21 Illustrations, black and white; X, 85 p. 21 illus.
Verlagsort	New York
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
ISBN-10	1-4939-0532-5 / 1493905325
ISBN-13	978-1-4939-0532-4 / 9781493905324
Zustand	Neuware