Mathematical methods for signal and image analysis and representation

Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a s...

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Glavni avtor: Florack, Luc (Éditeur intellectuel)
Drugi avtorji: Duits, Remco (Éditeur intellectuel), Jongbloed, Geurt (Éditeur intellectuel), van Lieshout, Marie-Colette (Éditeur intellectuel), Davies, Laurie (Éditeur intellectuel), van Lieshout, Marie-Colette, 19..- (Éditeur intellectuel)
Format: Livre numérique
Jezik:Anglais
Izdano: London : Springer London [20..].
Cham : Springer Nature
Izdaja:1st ed. 2012.
Serija:Computational Imaging and Vision 41
Teme:
Online dostop:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Sporočilo: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Mathematical methods for signal and image analysis and representation, edité par Luc Florack, Marie-Colette van Lieshout, Remco Duits, Laurie Davies, London, Springer, 2012, 1 vol. (XII-317 p.)., Computational imaging and vision, 978-1-447-12352-1
• Mathematical Methods for Signal and Image Analysis and Representation, Texte imprimé, 9781447158905
• Mathematical methods for signal and image analysis and representation, edité par Luc Florack, Marie-Colette van Lieshout, Remco Duits, Laurie Davies, London, Springer, 2012, 1 vol. (XII-317 p.)., Computational imaging and vision, 978-1-447-12352-1
• Mathematical Methods for Signal and Image Analysis and Representation, Texte imprimé, 9781447123545
Kazalo:
  • A Short Introduction to Diffusion-like Methods Adaptive Filtering using Channel Representations 3D-Coherence-Enhancing Diffusion Filtering for Matrix Fields Structural Adaptive Smoothing: Principles and Applications in Imaging SPD Tensors Regularization via Iwasawa Decomposition Sparse Representation of Video Data by Adaptive Tetrahedralizations Continuous Diffusion Wavelet Transforms and Scale Space over Euclidean Spaces and Noncommutative Lie Groups Left Invariant Evolution Equations on Gabor Transforms Scale Space Representations Locally Adapted to the Geometry of Base and Target Manifold An A Priori Model of Line Propagation Local Statistics on Shape Diffeomorphisms using a Depth Potential Function Preserving Time Structures while Denoising a Dynamical Image Interacting Adaptive Filters for Multiple Objects Detection Visual Data Recognition and Modeling based on Local Markovian Models Locally Specified Polygonal Markov Fields for Image Segmentation Regularization with Approximated L2 Maximum Entropy Method.