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Feature extraction & image processing for computer vision [[electronic resource] /] / Mark S. Nixon, Alberto S. Aguado
| Feature extraction & image processing for computer vision [[electronic resource] /] / Mark S. Nixon, Alberto S. Aguado |
| Autore | Nixon Mark S |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Oxford, : Academic, 2012 |
| Descrizione fisica | 1 online resource (628 p.) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
AguadoAlberto S
NixonMark S |
| Soggetto topico |
Computer vision
Computer vision - Mathematics Pattern recognition systems Image processing - Digital techniques |
| Soggetto genere / forma | Electronic books. |
| ISBN | 0-12-397824-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Feature Extraction & Image Processing for Computer Vision; Copyright page; Contents; Preface; What is new in the third edition?; Why did we write this book?; The book and its support; In gratitude; Final message; About the authors; 1 Introduction; 1.1 Overview; 1.2 Human and computer vision; 1.3 The human vision system; 1.3.1 The eye; 1.3.2 The neural system; 1.3.3 Processing; 1.4 Computer vision systems; 1.4.1 Cameras; 1.4.2 Computer interfaces; 1.4.3 Processing an image; 1.5 Mathematical systems; 1.5.1 Mathematical tools; 1.5.2 Hello Matlab, hello images!; 1.5.3 Hello Mathcad!
1.6 Associated literature1.6.1 Journals, magazines, and conferences; 1.6.2 Textbooks; 1.6.3 The Web; 1.7 Conclusions; 1.8 References; 2 Images, sampling, and frequency domain processing; 2.1 Overview; 2.2 Image formation; 2.3 The Fourier transform; 2.4 The sampling criterion; 2.5 The discrete Fourier transform; 2.5.1 1D transform; 2.5.2 2D transform; 2.6 Other properties of the Fourier transform; 2.6.1 Shift invariance; 2.6.2 Rotation; 2.6.3 Frequency scaling; 2.6.4 Superposition (linearity); 2.7 Transforms other than Fourier; 2.7.1 Discrete cosine transform; 2.7.2 Discrete Hartley transform 2.7.3 Introductory wavelets2.7.3.1 Gabor wavelet; 2.7.3.2 Haar wavelet; 2.7.4 Other transforms; 2.8 Applications using frequency domain properties; 2.9 Further reading; 2.10 References; 3 Basic image processing operations; 3.1 Overview; 3.2 Histograms; 3.3 Point operators; 3.3.1 Basic point operations; 3.3.2 Histogram normalization; 3.3.3 Histogram equalization; 3.3.4 Thresholding; 3.4 Group operations; 3.4.1 Template convolution; 3.4.2 Averaging operator; 3.4.3 On different template size; 3.4.4 Gaussian averaging operator; 3.4.5 More on averaging; 3.5 Other statistical operators 3.5.1 Median filter3.5.2 Mode filter; 3.5.3 Anisotropic diffusion; 3.5.4 Force field transform; 3.5.5 Comparison of statistical operators; 3.6 Mathematical morphology; 3.6.1 Morphological operators; 3.6.2 Gray-level morphology; 3.6.3 Gray-level erosion and dilation; 3.6.4 Minkowski operators; 3.7 Further reading; 3.8 References; 4 Low-level feature extraction (including edge detection); 4.1 Overview; 4.2 Edge detection; 4.2.1 First-order edge-detection operators; 4.2.1.1 Basic operators; 4.2.1.2 Analysis of the basic operators; 4.2.1.3 Prewitt edge-detection operator 4.2.1.4 Sobel edge-detection operator4.2.1.5 The Canny edge detector; 4.2.2 Second-order edge-detection operators; 4.2.2.1 Motivation; 4.2.2.2 Basic operators: the Laplacian; 4.2.2.3 The Marr-Hildreth operator; 4.2.3 Other edge-detection operators; 4.2.4 Comparison of edge-detection operators; 4.2.5 Further reading on edge detection; 4.3 Phase congruency; 4.4 Localized feature extraction; 4.4.1 Detecting image curvature (corner extraction); 4.4.1.1 Definition of curvature; 4.4.1.2 Computing differences in edge direction; 4.4.1.3 Measuring curvature by changes in intensity (differentiation) 4.4.1.4 Moravec and Harris detectors |
| Record Nr. | UNINA-9910462068503321 |
Nixon Mark S
|
||
| Oxford, : Academic, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Feature extraction & image processing for computer vision [[electronic resource] /] / Mark S. Nixon, Alberto S. Aguado
| Feature extraction & image processing for computer vision [[electronic resource] /] / Mark S. Nixon, Alberto S. Aguado |
| Autore | Nixon Mark S |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Oxford, : Academic, 2012 |
| Descrizione fisica | 1 online resource (628 p.) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
AguadoAlberto S
NixonMark S |
| Soggetto topico |
Computer vision
Computer vision - Mathematics Pattern recognition systems Image processing - Digital techniques |
| ISBN | 0-12-397824-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Feature Extraction & Image Processing for Computer Vision; Copyright page; Contents; Preface; What is new in the third edition?; Why did we write this book?; The book and its support; In gratitude; Final message; About the authors; 1 Introduction; 1.1 Overview; 1.2 Human and computer vision; 1.3 The human vision system; 1.3.1 The eye; 1.3.2 The neural system; 1.3.3 Processing; 1.4 Computer vision systems; 1.4.1 Cameras; 1.4.2 Computer interfaces; 1.4.3 Processing an image; 1.5 Mathematical systems; 1.5.1 Mathematical tools; 1.5.2 Hello Matlab, hello images!; 1.5.3 Hello Mathcad!
1.6 Associated literature1.6.1 Journals, magazines, and conferences; 1.6.2 Textbooks; 1.6.3 The Web; 1.7 Conclusions; 1.8 References; 2 Images, sampling, and frequency domain processing; 2.1 Overview; 2.2 Image formation; 2.3 The Fourier transform; 2.4 The sampling criterion; 2.5 The discrete Fourier transform; 2.5.1 1D transform; 2.5.2 2D transform; 2.6 Other properties of the Fourier transform; 2.6.1 Shift invariance; 2.6.2 Rotation; 2.6.3 Frequency scaling; 2.6.4 Superposition (linearity); 2.7 Transforms other than Fourier; 2.7.1 Discrete cosine transform; 2.7.2 Discrete Hartley transform 2.7.3 Introductory wavelets2.7.3.1 Gabor wavelet; 2.7.3.2 Haar wavelet; 2.7.4 Other transforms; 2.8 Applications using frequency domain properties; 2.9 Further reading; 2.10 References; 3 Basic image processing operations; 3.1 Overview; 3.2 Histograms; 3.3 Point operators; 3.3.1 Basic point operations; 3.3.2 Histogram normalization; 3.3.3 Histogram equalization; 3.3.4 Thresholding; 3.4 Group operations; 3.4.1 Template convolution; 3.4.2 Averaging operator; 3.4.3 On different template size; 3.4.4 Gaussian averaging operator; 3.4.5 More on averaging; 3.5 Other statistical operators 3.5.1 Median filter3.5.2 Mode filter; 3.5.3 Anisotropic diffusion; 3.5.4 Force field transform; 3.5.5 Comparison of statistical operators; 3.6 Mathematical morphology; 3.6.1 Morphological operators; 3.6.2 Gray-level morphology; 3.6.3 Gray-level erosion and dilation; 3.6.4 Minkowski operators; 3.7 Further reading; 3.8 References; 4 Low-level feature extraction (including edge detection); 4.1 Overview; 4.2 Edge detection; 4.2.1 First-order edge-detection operators; 4.2.1.1 Basic operators; 4.2.1.2 Analysis of the basic operators; 4.2.1.3 Prewitt edge-detection operator 4.2.1.4 Sobel edge-detection operator4.2.1.5 The Canny edge detector; 4.2.2 Second-order edge-detection operators; 4.2.2.1 Motivation; 4.2.2.2 Basic operators: the Laplacian; 4.2.2.3 The Marr-Hildreth operator; 4.2.3 Other edge-detection operators; 4.2.4 Comparison of edge-detection operators; 4.2.5 Further reading on edge detection; 4.3 Phase congruency; 4.4 Localized feature extraction; 4.4.1 Detecting image curvature (corner extraction); 4.4.1.1 Definition of curvature; 4.4.1.2 Computing differences in edge direction; 4.4.1.3 Measuring curvature by changes in intensity (differentiation) 4.4.1.4 Moravec and Harris detectors |
| Record Nr. | UNINA-9910790326903321 |
|
Nixon Mark S
|
||
| Oxford, : Academic, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Feature extraction & image processing for computer vision / / Mark S. Nixon, Alberto S. Aguado
| Feature extraction & image processing for computer vision / / Mark S. Nixon, Alberto S. Aguado |
| Autore | Nixon Mark S |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Oxford, : Academic, 2012 |
| Descrizione fisica | 1 online resource (628 p.) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
AguadoAlberto S
NixonMark S |
| Soggetto topico |
Computer vision
Computer vision - Mathematics Pattern recognition systems Image processing - Digital techniques |
| ISBN | 0-12-397824-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Feature Extraction & Image Processing for Computer Vision; Copyright page; Contents; Preface; What is new in the third edition?; Why did we write this book?; The book and its support; In gratitude; Final message; About the authors; 1 Introduction; 1.1 Overview; 1.2 Human and computer vision; 1.3 The human vision system; 1.3.1 The eye; 1.3.2 The neural system; 1.3.3 Processing; 1.4 Computer vision systems; 1.4.1 Cameras; 1.4.2 Computer interfaces; 1.4.3 Processing an image; 1.5 Mathematical systems; 1.5.1 Mathematical tools; 1.5.2 Hello Matlab, hello images!; 1.5.3 Hello Mathcad!
1.6 Associated literature1.6.1 Journals, magazines, and conferences; 1.6.2 Textbooks; 1.6.3 The Web; 1.7 Conclusions; 1.8 References; 2 Images, sampling, and frequency domain processing; 2.1 Overview; 2.2 Image formation; 2.3 The Fourier transform; 2.4 The sampling criterion; 2.5 The discrete Fourier transform; 2.5.1 1D transform; 2.5.2 2D transform; 2.6 Other properties of the Fourier transform; 2.6.1 Shift invariance; 2.6.2 Rotation; 2.6.3 Frequency scaling; 2.6.4 Superposition (linearity); 2.7 Transforms other than Fourier; 2.7.1 Discrete cosine transform; 2.7.2 Discrete Hartley transform 2.7.3 Introductory wavelets2.7.3.1 Gabor wavelet; 2.7.3.2 Haar wavelet; 2.7.4 Other transforms; 2.8 Applications using frequency domain properties; 2.9 Further reading; 2.10 References; 3 Basic image processing operations; 3.1 Overview; 3.2 Histograms; 3.3 Point operators; 3.3.1 Basic point operations; 3.3.2 Histogram normalization; 3.3.3 Histogram equalization; 3.3.4 Thresholding; 3.4 Group operations; 3.4.1 Template convolution; 3.4.2 Averaging operator; 3.4.3 On different template size; 3.4.4 Gaussian averaging operator; 3.4.5 More on averaging; 3.5 Other statistical operators 3.5.1 Median filter3.5.2 Mode filter; 3.5.3 Anisotropic diffusion; 3.5.4 Force field transform; 3.5.5 Comparison of statistical operators; 3.6 Mathematical morphology; 3.6.1 Morphological operators; 3.6.2 Gray-level morphology; 3.6.3 Gray-level erosion and dilation; 3.6.4 Minkowski operators; 3.7 Further reading; 3.8 References; 4 Low-level feature extraction (including edge detection); 4.1 Overview; 4.2 Edge detection; 4.2.1 First-order edge-detection operators; 4.2.1.1 Basic operators; 4.2.1.2 Analysis of the basic operators; 4.2.1.3 Prewitt edge-detection operator 4.2.1.4 Sobel edge-detection operator4.2.1.5 The Canny edge detector; 4.2.2 Second-order edge-detection operators; 4.2.2.1 Motivation; 4.2.2.2 Basic operators: the Laplacian; 4.2.2.3 The Marr-Hildreth operator; 4.2.3 Other edge-detection operators; 4.2.4 Comparison of edge-detection operators; 4.2.5 Further reading on edge detection; 4.3 Phase congruency; 4.4 Localized feature extraction; 4.4.1 Detecting image curvature (corner extraction); 4.4.1.1 Definition of curvature; 4.4.1.2 Computing differences in edge direction; 4.4.1.3 Measuring curvature by changes in intensity (differentiation) 4.4.1.4 Moravec and Harris detectors |
| Altri titoli varianti | Feature extraction and image processing for computer vision |
| Record Nr. | UNINA-9910969419303321 |
|
Nixon Mark S
|
||
| Oxford, : Academic, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Markov random fields for vision and image processing [[electronic resource] /] / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
| Markov random fields for vision and image processing [[electronic resource] /] / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, c2011 |
| Descrizione fisica | 1 online resource (472 p.) |
| Disciplina | 006.3/70151 |
| Altri autori (Persone) |
BlakeAndrew <1956->
KohliPushmeet RotherCarsten |
| Soggetto topico |
Image processing - Mathematics
Computer graphics - Mathematics Computer vision - Mathematics Markov random fields |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-25865-X
9786613258656 0-262-29835-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover ; Contents; 1 Introduction to Markov Random Fields; I Algorithms for Inference of MAP Estimates for MRFs; 2 Basic Graph Cut Algorithms; 3 Optimizing Multilabel MRFs Using Move-Making Algorithms; 4 Optimizing Multilabel MRFs with Convex and Truncated Convex Priors; 5 Loopy Belief Propagation, Mean Field Theory, and Bethe Approximations; 6 Linear Programming and Variants of Belief Propagation; II Applications of MRFs, including Segmentation; 7 Interactive Foreground Extraction; 8 Continuous-Valued MRF for Image Segmentation; 9 Bilayer Segmentation of Video
10 MRFs for Superresolution and Texture Synthesis11 A Comparative Study of Energy Minimization Methods for MRFs; III Further Topics: Inference, Parameter Learning, and Continuous Models; 12 Convex Relaxation Techniques for Segmentation, Stereo, and Multiview Reconstruction; 13 Learning Parameters in Continuous-Valued Markov Random Fields; 14 Message Passing with Continuous Latent Variables; 15 Learning Large-Margin Random Fields Using Graph Cuts; 16 Analyzing Convex Relaxations for MAP Estimation; 17 MAP Inference by Fast Primal-Dual Linear Programming 18 Fusion-Move Optimization for MRFs with an Extensive Label SpaceIV Higher-Order MRFs and Global Constraints; 19 Field of Experts; 20 Enforcing Label Consistency Using Higher-Order Potentials; 21 Exact Optimization for Markov Random Fields with Nonlocal Parameters; 22 Graph Cut-Based Image Segmentation with Connectivity Priors; V Advanced Applications of MRFs; 23 Symmetric Stereo Matching for Occlusion Handling; 24 Steerable Random Fields for Image Restoration; 25 Markov Random Fields for Object Detection; 26 SIFT Flow; 27 Unwrap Mosaics; Bibliography; Contributors; Index |
| Record Nr. | UNINA-9910456890503321 |
| Cambridge, Mass., : MIT Press, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother
| Markov random fields for vision and image processing / / edited by Andrew Blake, Pushmeet Kohli, and Carsten Rother |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, ©2011 |
| Descrizione fisica | 1 online resource (472 p.) |
| Disciplina | 006.3/70151 |
| Altri autori (Persone) |
BlakeAndrew <1956->
KohliPushmeet RotherCarsten |
| Soggetto topico |
Image processing - Mathematics
Computer graphics - Mathematics Computer vision - Mathematics Markov random fields |
| Soggetto non controllato |
NEUROSCIENCE/Visual Neuroscience
COMPUTER SCIENCE/General |
| ISBN |
1-283-25865-X
9786613258656 0-262-29835-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover ; Contents; 1 Introduction to Markov Random Fields; I Algorithms for Inference of MAP Estimates for MRFs; 2 Basic Graph Cut Algorithms; 3 Optimizing Multilabel MRFs Using Move-Making Algorithms; 4 Optimizing Multilabel MRFs with Convex and Truncated Convex Priors; 5 Loopy Belief Propagation, Mean Field Theory, and Bethe Approximations; 6 Linear Programming and Variants of Belief Propagation; II Applications of MRFs, including Segmentation; 7 Interactive Foreground Extraction; 8 Continuous-Valued MRF for Image Segmentation; 9 Bilayer Segmentation of Video
10 MRFs for Superresolution and Texture Synthesis11 A Comparative Study of Energy Minimization Methods for MRFs; III Further Topics: Inference, Parameter Learning, and Continuous Models; 12 Convex Relaxation Techniques for Segmentation, Stereo, and Multiview Reconstruction; 13 Learning Parameters in Continuous-Valued Markov Random Fields; 14 Message Passing with Continuous Latent Variables; 15 Learning Large-Margin Random Fields Using Graph Cuts; 16 Analyzing Convex Relaxations for MAP Estimation; 17 MAP Inference by Fast Primal-Dual Linear Programming 18 Fusion-Move Optimization for MRFs with an Extensive Label SpaceIV Higher-Order MRFs and Global Constraints; 19 Field of Experts; 20 Enforcing Label Consistency Using Higher-Order Potentials; 21 Exact Optimization for Markov Random Fields with Nonlocal Parameters; 22 Graph Cut-Based Image Segmentation with Connectivity Priors; V Advanced Applications of MRFs; 23 Symmetric Stereo Matching for Occlusion Handling; 24 Steerable Random Fields for Image Restoration; 25 Markov Random Fields for Object Detection; 26 SIFT Flow; 27 Unwrap Mosaics; Bibliography; Contributors; Index |
| Record Nr. | UNINA-9910781666803321 |
| Cambridge, Mass., : MIT Press, ©2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimization for computer vision : an introduction to core concepts and methods / / Marco Alexander Treiber
| Optimization for computer vision : an introduction to core concepts and methods / / Marco Alexander Treiber |
| Autore | Treiber Marco Alexander |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, : Springer, 2013 |
| Descrizione fisica | 1 online resource (xi, 257 pages) : illustrations (some color) |
| Disciplina | 006.37 |
| Collana | Advances in computer vision and pattern recognition |
| Soggetto topico |
Computer vision - Mathematics
Mathematical optimization |
| ISBN | 1-4471-5283-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Continuous Optimization -- Linear Programming and the Simplex Method -- Variational Methods -- Correspondence Problems -- Graph Cuts -- Dynamic Programming. |
| Record Nr. | UNINA-9910437579303321 |
|
Treiber Marco Alexander
|
||
| New York, : Springer, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Scale space and variational methods in computer vision : second international conference, SSVM 2009, Voss, Norway, June 1-5, 2009 ; proceedings / / Xue-Cheng Tai ... [et al.] (eds.)
| Scale space and variational methods in computer vision : second international conference, SSVM 2009, Voss, Norway, June 1-5, 2009 ; proceedings / / Xue-Cheng Tai ... [et al.] (eds.) |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, : Springer, 2009 |
| Descrizione fisica | 1 online resource (XIV, 870 p.) |
| Disciplina | 006.37 |
| Altri autori (Persone) | TaiXue-Cheng |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Computer vision - Mathematics
Computer vision - Methodology Image processing - Digital techniques |
| ISBN |
1-280-38295-3
9786613560865 3-642-02256-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Segmentation and Detection -- Graph Cut Optimization for the Piecewise Constant Level Set Method Applied to Multiphase Image Segmentation -- Tubular Anisotropy Segmentation -- An Unconstrained Multiphase Thresholding Approach for Image Segmentation -- Extraction of the Intercellular Skeleton from 2D Images of Embryogenesis Using Eikonal Equation and Advective Subjective Surface Method -- On Level-Set Type Methods for Recovering Piecewise Constant Solutions of Ill-Posed Problems -- The Nonlinear Tensor Diffusion in Segmentation of Meaningful Biological Structures from Image Sequences of Zebrafish Embryogenesis -- Composed Segmentation of Tubular Structures by an Anisotropic PDE Model -- Extrapolation of Vector Fields Using the Infinity Laplacian and with Applications to Image Segmentation -- A Schrödinger Equation for the Fast Computation of Approximate Euclidean Distance Functions -- Semi-supervised Segmentation Based on Non-local Continuous Min-Cut -- Momentum Based Optimization Methods for Level Set Segmentation -- Optimization of Divergences within the Exponential Family for Image Segmentation -- Convex Multi-class Image Labeling by Simplex-Constrained Total Variation -- Geodesically Linked Active Contours: Evolution Strategy Based on Minimal Paths -- Validation of Watershed Regions by Scale-Space Statistics -- Adaptation of Eikonal Equation over Weighted Graph -- A Variational Model for Interactive Shape Prior Segmentation and Real-Time Tracking -- Image Enhancement and Reconstruction -- A Nonlinear Probabilistic Curvature Motion Filter for Positron Emission Tomography Images -- Finsler Geometry on Higher Order Tensor Fields and Applications to High Angular Resolution Diffusion Imaging -- Bregman-EM-TV Methods with Application to Optical Nanoscopy -- PDE-Driven Adaptive Morphology for Matrix Fields -- On Semi-implicit Splitting Schemes for the Beltrami Color Flow -- Multi-scale Total Variation with Automated Regularization Parameter Selection for Color Image Restoration -- Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients -- Projected Gradient Based Color Image Decomposition -- A Dual Formulation of the TV-Stokes Algorithm for Image Denoising -- Anisotropic Regularization for Inverse Problems with Application to the Wiener Filter with Gaussian and Impulse Noise -- Locally Adaptive Total Variation Regularization -- Basic Image Features (BIFs) Arising from Approximate Symmetry Type -- An Anisotropic Fourth-Order Partial Differential Equation for Noise Removal -- Enhancement of Blurred and Noisy Images Based on an Original Variant of the Total Variation -- Coarse-to-Fine Image Reconstruction Based on Weighted Differential Features and Background Gauge Fields -- Edge-Enhanced Image Reconstruction Using (TV) Total Variation and Bregman Refinement -- Nonlocal Variational Image Deblurring Models in the Presence of Gaussian or Impulse Noise -- A Geometric PDE for Interpolation of M-Channel Data -- An Edge-Preserving Multilevel Method for Deblurring, Denoising, and Segmentation -- Fast Dejittering for Digital Video Frames -- Sparsity Regularization for Radon Measures -- Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage -- Anisotropic Smoothing Using Double Orientations -- Image Denoising Using TV-Stokes Equation with an Orientation-Matching Minimization -- Augmented Lagrangian Method, Dual Methods and Split Bregman Iteration for ROF Model -- The Convergence of a Central-Difference Discretization of Rudin-Osher-Fatemi Model for Image Denoising -- Theoretical Foundations for Discrete Forward-and-Backward Diffusion Filtering -- L 0-Norm and Total Variation for Wavelet Inpainting -- Total-Variation Based Piecewise Affine Regularization -- Image Denoising by Harmonic Mean Curvature Flow -- Motion Analysis, Optical Flow, Registration and Tracking -- Tracking Closed Curves with Non-linear Stochastic Filters -- A Multi-scale Feature Based Optic Flow Method for 3D Cardiac Motion Estimation -- A Combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother -- A Scale-Space Approach to Landmark Constrained Image Registration -- A Variational Approach for Volume-to-Slice Registration -- Hyperbolic Numerics for Variational Approaches to Correspondence Problems -- Surfaces and Shapes -- From a Single Point to a Surface Patch by Growing Minimal Paths -- Optimization of Convex Shapes: An Approach to Crystal Shape Identification -- An Implicit Method for Interpolating Two Digital Closed Curves on Parallel Planes -- Pose Invariant Shape Prior Segmentation Using Continuous Cuts and Gradient Descent on Lie Groups -- A Non-local Approach to Shape from Ambient Shading -- An Elasticity Approach to Principal Modes of Shape Variation -- Pre-image as Karcher Mean Using Diffusion Maps: Application to Shape and Image Denoising -- Fast Shape from Shading for Phong-Type Surfaces -- Generic Scene Recovery Using Multiple Images -- Scale Space and Feature Extraction -- Highly Accurate PDE-Based Morphology for General Structuring Elements -- Computational Geometry-Based Scale-Space and Modal Image Decomposition -- Highlight on a Feature Extracted at Fine Scales: The Pointwise Lipschitz Regularity -- Line Enhancement and Completion via Linear Left Invariant Scale Spaces on SE(2) -- Spatio-Featural Scale-Space -- Scale Spaces on the 3D Euclidean Motion Group for Enhancement of HARDI Data -- On the Rate of Structural Change in Scale Spaces -- Transitions of a Multi-scale Image Hierarchy Tree -- Local Scale Measure for Remote Sensing Images. |
| Altri titoli varianti | SSVM 2009 |
| Record Nr. | UNINA-9910484281703321 |
| Berlin, : Springer, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Variational, geometric, and level set methods in computer vision : Third International Workshop, VLSM 2005, Beijing, China, October 16, 2005 : proceedings / / Nikos Paragios ... [et al.] (eds.)
| Variational, geometric, and level set methods in computer vision : Third International Workshop, VLSM 2005, Beijing, China, October 16, 2005 : proceedings / / Nikos Paragios ... [et al.] (eds.) |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, : Springer, c2005 |
| Descrizione fisica | 1 online resource (XII, 372 p.) |
| Disciplina |
006.6
006.37 |
| Altri autori (Persone) | ParagiosNikos |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Computer vision - Mathematics
Computer vision - Methodology Image processing - Digital techniques |
| Classificazione | 54.74 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Study of Non-smooth Convex Flow Decomposition -- Denoising Tensors via Lie Group Flows -- Nonlinear Inverse Scale Space Methods for Image Restoration -- Towards PDE-Based Image Compression -- Color Image Deblurring with Impulsive Noise -- Using an Oriented PDE to Repair Image Textures -- Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L 1 Functional -- Structure-Texture Decomposition by a TV-Gabor Model -- From Inpainting to Active Contours -- Sobolev Active Contours -- Advances in Variational Image Segmentation Using AM-FM Models: Regularized Demodulation and Probabilistic Cue Integration -- Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision -- Global Minimization of the Active Contour Model with TV-Inpainting and Two-Phase Denoising -- Combined Geometric-Texture Image Classification -- Heuristically Driven Front Propagation for Geodesic Paths Extraction -- Trimap Segmentation for Fast and User-Friendly Alpha Matting -- Uncertainty-Driven Non-parametric Knowledge-Based Segmentation: The Corpus Callosum Case -- Dynamical Statistical Shape Priors for Level Set Based Sequence Segmentation -- Non-rigid Shape Comparison of Implicitly-Defined Curves -- Incorporating Rigid Structures in Non-rigid Registration Using Triangular B-Splines -- Geodesic Image Interpolation: Parameterizing and Interpolating Spatiotemporal Images -- A Variational Approach for Object Contour Tracking -- Implicit Free-Form-Deformations for Multi-frame Segmentation and Tracking -- A Surface Reconstruction Method for Highly Noisy Point Clouds -- A C 1 Globally Interpolatory Spline of Arbitrary Topology -- Solving PDEs on Manifolds with Global Conformal Parametriazation -- Fast Marching Method for Generic Shape from Shading -- A Gradient Descent Procedure for Variational Dynamic Surface Problems with Constraints -- Regularization of Mappings Between Implicit Manifolds of Arbitrary Dimension and Codimension -- Lens Distortion Calibration Using Level Sets. |
| Altri titoli varianti | VLSM 2005 |
| Record Nr. | UNINA-9910483821303321 |
| Berlin, : Springer, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
