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Scale-Space Theory in Computer Vision

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Cover of 'Scale-Space Theory in Computer Vision'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction and overview
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    Chapter 2 Linear scale-space and related multi-scale representations
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    Chapter 3 Scale-space for 1-D discrete signals
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    Chapter 4 Scale-space for N-D discrete signals
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    Chapter 5 Discrete derivative approximations with scale-space properties
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    Chapter 6 Feature detection in scale-space
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    Chapter 7 The scale-space primal sketch
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    Chapter 8 Behaviour of image structures in scale-space: Deep structure
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    Chapter 9 Algorithm for computing the scale-space primal sketch
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    Chapter 10 Detecting salient blob-like image structures and their scales
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    Chapter 11 Guiding early visual processing with qualitative scale and region information
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    Chapter 12 Summary and discussion
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    Chapter 13 Scale selection for differential operators
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    Chapter 14 Direct computation of shape cues by scale-space operations
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    Chapter 15 Non-uniform smoothing
Attention for Chapter 5: Discrete derivative approximations with scale-space properties
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