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...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , , , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
London :
Springer London,
2012.
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| Σειρά: | Computational Imaging and Vision,
41 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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. .
