TY  - BOOK
AU  - Montegranario,Hebert
AU  - Espinosa,Jairo
ED  - SpringerLink (Online service)
TI  - Variational Regularization of 3D Data: Experiments with MATLAB® 
T2  - SpringerBriefs in Computer Science,
SN  - 9781493905331
AV  - TA1637-1638 
U1  - 006.6 23
PY  - 2014///
CY  - New York, NY
PB  - Springer New York, Imprint: Springer
KW  - Computer science
KW  - Computer simulation
KW  - Computer vision
KW  - Computer Science
KW  - Image Processing and Computer Vision
KW  - Math Applications in Computer Science
KW  - Simulation and Modeling
N1  - 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
N2  - 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
UR  - http://dx.doi.org/10.1007/978-1-4939-0533-1
ER  -