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Scale Space and Variational Methods in Computer Vision

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Cover of 'Scale Space and Variational Methods in Computer Vision'

Table of Contents

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    Book Overview
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    Chapter 1 The Fractional Harris-Laplace Feature Detector
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    Chapter 2 Macrocanonical Models for Texture Synthesis
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    Chapter 3 Finding Structure in Point Cloud Data with the Robust Isoperimetric Loss
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    Chapter 4 Deep Eikonal Solvers
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    Chapter 5 A Splitting-Based Algorithm for Multi-view Stereopsis of Textureless Objects
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    Chapter 6 Pseudodifferential Inpainting: The Missing Link Between PDE- and RBF-Based Interpolation
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    Chapter 7 Towards PDE-Based Video Compression with Optimal Masks and Optic Flow
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    Chapter 8 Compressing Audio Signals with Inpainting-Based Sparsification
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    Chapter 9 Alternate Structural-Textural Video Inpainting for Spot Defects Correction in Movies
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    Chapter 10 Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems
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    Chapter 11 Refitting Solutions Promoted by $$\ell _{12}$$ Sparse Analysis Regularizations with Block Penalties
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    Chapter 12 An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data
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    Chapter 13 A New Iterative Method for CT Reconstruction with Uncertain View Angles
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    Chapter 14 Time Discrete Geodesics in Deep Feature Spaces for Image Morphing
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    Chapter 15 Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphs
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    Chapter 16 The Convex-Hull-Stripping Median Approximates Affine Curvature Motion
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    Chapter 17 Total Variation and Mean Curvature PDEs on the Space of Positions and Orientations
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    Chapter 18 A Variational Convex Hull Algorithm
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    Chapter 19 PDE Evolutions for M-Smoothers: From Common Myths to Robust Numerics
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    Chapter 20 Variational Registration of Multiple Images with the SVD Based $$\mathrm {S}q\mathrm {N}$$ Distance Measure
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    Chapter 21 Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration
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    Chapter 22 Variational Image Registration for Inhomogeneous-Resolution Pairs
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    Chapter 23 Computing Nonlinear Eigenfunctions via Gradient Flow Extinction
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    Chapter 24 Sparsification Scale-Spaces
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    Chapter 25 Stable Explicit p-Laplacian Flows Based on Nonlinear Eigenvalue Analysis
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    Chapter 26 Provably Scale-Covariant Networks from Oriented Quasi Quadrature Measures in Cascade
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    Chapter 27 A Fast Multi-layer Approximation to Semi-discrete Optimal Transport
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    Chapter 28 Global Similarity with Additive Smoothness for Spectral Segmentation
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    Chapter 29 Segmentation of 2D and 3D Objects with Intrinsically Similarity Invariant Shape Regularisers
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    Chapter 30 Lattice Metric Space Application to Grain Defect Detection
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    Chapter 31 Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
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    Chapter 32 Direct MRI Segmentation from k-Space Data by Iterative Potts Minimization
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    Chapter 33 A Balanced Phase Field Model for Active Contours
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    Chapter 34 Unsupervised Labeling by Geometric and Spatially Regularized Self-assignment
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    Chapter 35 Aorta Centerline Smoothing and Registration Using Variational Models
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    Chapter 36 A Connection Between Image Processing and Artificial Neural Networks Layers Through a Geometric Model of Visual Perception
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    Chapter 37 A Cortical-Inspired Model for Orientation-Dependent Contrast Perception: A Link with Wilson-Cowan Equations
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    Chapter 38 A Total Variation Based Regularizer Promoting Piecewise-Lipschitz Reconstructions
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    Chapter 39 A Non-convex Nonseparable Approach to Single-Molecule Localization Microscopy
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    Chapter 40 Preservation of Piecewise Constancy under TV Regularization with Rectilinear Anisotropy
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    Chapter 41 Total Directional Variation for Video Denoising
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    Chapter 42 Joint CNN and Variational Model for Fully-Automatic Image Colorization
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    Chapter 43 A Variational Perspective on the Assignment Flow
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    Chapter 44 Functional Liftings of Vectorial Variational Problems with Laplacian Regularization
Attention for Chapter 24: Sparsification Scale-Spaces
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Chapter title
Sparsification Scale-Spaces
Chapter number 24
Book title
Scale Space and Variational Methods in Computer Vision
Published by
Springer, Cham, June 2019
DOI 10.1007/978-3-030-22368-7_24
Book ISBNs
978-3-03-022367-0, 978-3-03-022368-7
Authors

Marcelo Cárdenas, Pascal Peter, Joachim Weickert, Cárdenas, Marcelo, Peter, Pascal, Weickert, Joachim