Information technology and the productivity paradox: assessing the value of investing in IT/ Henry C. Lucas

Includes bibliographical references (p. 217-221) and index.

1 Introduction
1.1 Biological information processing 3
1.2 Information in images ^
1.3 Vision as information processing 13
2 Imaging
2.1 Intensities
2.2 Imaging systems
2.3 Perspective projection 31
2.4 Eye movements
II Contrast, Form, and Color 47
3 Representation and processing of images 49
3.1 Examples
3.2 Sampling
3.3 Image processing
3.4 Resolution
4 Edge detection *^3
4.1 The significance of edges 73
4.2 Edge detection in one dimension . . . ' 78
4.3 Edge detection in two dimensions 88
5 Color and color constancy 94
5.1 The color of isolated points of light 95
5.2 Color in images
viii CONTENTS
III Depth Perception 119
6 Stereoscopic vision 121
6.1 Differences between images due to parallax 121
6.2 Stereoscopic geometry (binocular perspective) 124
6.3 Stereo algorithms 133
6.4 Neural networks 141
6.5 Psychophysics 142
7 Shape from shading 140
7.1 Psychophysics I47
7.2 Problem statement I49
7.3 One-dimensional "images"
7.4 Shape from shading in two dimensions I57
8 Texture and surface orientation 162
8.1 Texture and texture gradients
8.2 Regular patterns: Vanishing points
8.3 Stochastic patterns 1; Density gradient 100
8.4 Statistical patterns 2: Shape gradient
IV Motion 177'
9 Motion detection l^-g
9.1 Problem statement
9.2 The correlation detector
9.3 The gradient detector
9.4 Orientation in the spatio-temporal image
9.5 Second-order motions
10 Optical flow 200
10.1 Information in the optical flow 200
10.2 Motion vector fields 201
10.3 Flow fields for observer motion 206
10.4 Recovering information from optical flow 218
11 Visual navigation 224
11.1 Path integration 224
11.2 Navigation using landmarks 228
11.3 Constructed environments 230
11.4 Neurophysiology of spatial memory - 241
CONTENTS ix
V Appendix 243
Glossary of mathematical terms 245
Mathematical symbols and units 263