Section IV: Image and Video Analysis

Chapters List

Chapter 4.1: Computational Models of Early Human Vision
Chapter 4.2: Multiscale Image Decompositions and Wavelets
Chapter 4.3: Random Field Models
Chapter 4.4: AM-FM Image Models Fundamental Techniques and Emerging Trends
Chapter 4.5: Image Noise Models
Chapter 4.6: Color and Multispectral Image Representation and Display
Chapter 4.7: Statistical Modeling of Photographic Images
Chapter 4.8: Statistical Methods for Image Segmentation
Chapter 4.9: Multiband Techniques for Texture Classification and Segmentation
Chapter 4.10: Video Segmentation
Chapter 4.11: 2D and 3D Motion Tracking in Digital Video
Chapter 4.12: Adaptive and Neural Methods for Image Segmentation
Chapter 4.13: Gradient and Laplacian Edge Detection
Chapter 4.14: Diffusion Partial Differential Equations for Edge Detection
Chapter 4.15: Shape Smoothing and PDEs
Chapter 4.16: PDEs for Morphological Scale Spaces and Eikonal Applications
Chapter 4.17: Geometric Active Contours for Image Segmentation
Chapter 4.18: Software for Image and Video Processing

Lawrence K. Cormack,
The University of Texas at Austin

"The nature of things, hidden in darkness, is revealed only by analogizing. This is achieved in such a way that by means of simpler machines, more easily accessible to the senses, we lay bare the more intricate." Marcello Malpighi, 1675

1 Introduction

1.1 Aim and Scope

The author of a short chapter on computational models of human vision is faced with an embarras de richesse. One wishes to make a choice between breadth and depth, but even this is virtually impossible within a reasonable space constraint. It is hoped that this chapter will serve as a brief overview for engineers...

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Handbook of Image and Video Processing

TABLE OF CONTENTS

Section IV: Image and Video Analysis

Chapters List

1 Introduction

1.1 Aim and Scope

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