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Front-End Vision and Multi-Scale Image Analysis

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Cover of 'Front-End Vision and Multi-Scale Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Apertures and the notion of scale
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    Chapter 2 Foundations of scale-space
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    Chapter 3 The Gaussian kernel
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    Chapter 4 Gaussian derivatives
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    Chapter 5 Multi-scale derivatives: implementations
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    Chapter 6 Differential structure of images
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    Chapter 7 Natural limits on observations
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    Chapter 8 Differentiation and regularization
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    Chapter 9 The front-end visual system — the retina
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    Chapter 10 A scale-space model for the retinal sampling
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    Chapter 11 The front-end visual system — LGN and cortex
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    Chapter 12 The front-end visual system — cortical columns
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    Chapter 13 Deep structure I. watershed segmentation
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    Chapter 14 Deep structure II. catastrophe theory
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    Chapter 15 Deep structure III. topological numbers
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    Chapter 16 Deblurring Gaussian blur
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    Chapter 17 Multi-scale optic flow
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    Chapter 18 Color differential structure
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    Chapter 19 Steerable kernels
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    Chapter 20 Scale-time
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    Chapter 21 Geometry-driven diffusion
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    Chapter 22 Epilog
Attention for Chapter 13: Deep structure I. watershed segmentation
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