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Geometry-Driven Diffusion in Computer Vision

Overview of attention for book
Geometry-Driven Diffusion in Computer Vision
Springer Netherlands

Table of Contents

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    Book Overview
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    Chapter 1 Linear Scale-Space I: Basic Theory
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    Chapter 2 Linear Scale-Space II: Early Visual Operations
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    Chapter 3 Anisotropic Diffusion
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    Chapter 4 Vector-Valued Diffusion
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    Chapter 5 Bayesian Rationale for the Variational Formulation
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    Chapter 6 Variational Problems with a Free Discontinuity Set
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    Chapter 7 Minimization of Energy Functional with Curve-Represented Edges
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    Chapter 8 Approximation, Computation, and Distortion in the Variational Formulation
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    Chapter 9 Coupled Geometry-Driven Diffusion Equations for Low-Level Vision
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    Chapter 10 Morphological Approach to Multiscale Analysis: From Principles to Equations
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    Chapter 11 Differential Invariant Signatures and Flows in Computer Vision: A Symmetry Group Approach
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    Chapter 12 On Optimal Control Methods in Computer Vision and Image Processing
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    Chapter 13 Nonlinear Scale-Space
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    Chapter 14 A Differential Geometric Approach to Anisotropic Diffusion
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    Chapter 15 Numerical Analysis of Geometry-Driven Diffusion Equations
Attention for Chapter 3: Anisotropic Diffusion
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