000 | 03196nam a22005535i 4500 | ||
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001 | 978-1-4939-0533-1 | ||
003 | DE-He213 | ||
005 | 20200421112226.0 | ||
007 | cr nn 008mamaa | ||
008 | 140314s2014 xxu| s |||| 0|eng d | ||
020 |
_a9781493905331 _9978-1-4939-0533-1 |
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024 | 7 |
_a10.1007/978-1-4939-0533-1 _2doi |
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050 | 4 | _aTA1637-1638 | |
050 | 4 | _aTA1634 | |
072 | 7 |
_aUYT _2bicssc |
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072 | 7 |
_aUYQV _2bicssc |
|
072 | 7 |
_aCOM012000 _2bisacsh |
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072 | 7 |
_aCOM016000 _2bisacsh |
|
082 | 0 | 4 |
_a006.6 _223 |
082 | 0 | 4 |
_a006.37 _223 |
100 | 1 |
_aMontegranario, Hebert. _eauthor. |
|
245 | 1 | 0 |
_aVariational Regularization of 3D Data _h[electronic resource] : _bExperiments with MATLAB� / _cby Hebert Montegranario, Jairo Espinosa. |
264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2014. |
|
300 |
_aX, 85 p. 21 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
505 | 0 | _a3D 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. | |
520 | _aVariational 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. | ||
650 | 0 | _aComputer science. | |
650 | 0 |
_aComputer science _xMathematics. |
|
650 | 0 | _aComputer simulation. | |
650 | 0 | _aImage processing. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aImage Processing and Computer Vision. |
650 | 2 | 4 | _aMath Applications in Computer Science. |
650 | 2 | 4 | _aSimulation and Modeling. |
700 | 1 |
_aEspinosa, Jairo. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781493905324 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4939-0533-1 |
912 | _aZDB-2-SCS | ||
942 | _cEBK | ||
999 |
_c57672 _d57672 |