Image Analysis for the Biological Sciences (Statistics in Practice)

Image Analysis for the Biological Sciences (Statistics in Practice)

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  • 製本 Hardcover:ハードカバー版/ページ数 250 p.
  • 言語 ENG,ENG
  • 商品コード 9780471937265
  • DDC分類 574.0285

Full Description


Covering the basics of quantitative image analysis - the extraction of information from data in the form of pictures - this study places special emphasis on methods relevant to environmental scientists. A number of practical examples from various forms of microscopy, medical imaging systems, remote sensing and contact prints will be introduced in this volume to demonstrate the diverse range of applications of image analysis. The nature of digital images and the terminology used is explained. Reference is made to extensions of multivariate and multi-temporal images. The appendix provides the reader with useful practical guidance on choosing hardware/software for a specific application.

Table of Contents

Preface                                            ix
Series Preface xi
Introduction 1 (22)
Why use a computer? 1 (14)
An example of image analysis 1 (2)
Human and computer interpretation of 3 (4)
images
Further examples 7 (8)
What are the data? 15 (4)
What does image analysis consist of? 19 (3)
Summary 22 (1)
Display 23 (24)
Binary display 24 (1)
Greyscale display 25 (7)
Perception of brightness 25 (1)
Display enhancement 26 (6)
Colour display 32 (7)
The physics and biology of colour 34 (1)
Pseudocolour 35 (1)
Direct allocation 36 (3)
Zooming and reduction 39 (3)
Registration 42 (2)
Summary 44 (3)
Filters 47 (46)
Linear filters in the spatial domain 49 (11)
Smoothing 50 (5)
Edge detection 55 (5)
Linear filters in the frequency domain 60 (18)
Theory of the Fourier transform 61 (4)
Filters already considered 65 (4)
New filters and image restoration 69 (9)
Nonlinear smoothing filters 78 (7)
Histogram-based filters 78 (5)
Spatially adaptive filters 83 (2)
Nonlinear edge-detection filters 85 (5)
Simple edge filters 85 (2)
Gradient filters 87 (3)
Summary 90 (3)
Segmentation 93 (32)
Thresholding 95 (18)
Histogram-based thresholding 97 (5)
Multivariate classifiers 102(5)
Contextual classifiers 107(6)
Edge-based segmentation 113(4)
Region-based segmentation 117(5)
Summary 122(3)
Mathematical Morphology 125(28)
Basic ideas 128(5)
Operations for size and shape 133(5)
Operations for connectivity 138(4)
Operations for texture 142(1)
Morphology for greyscale images 143(9)
Summary 152(1)
Measurement 153(32)
Measures of size 155(15)
Areas and moments 156(5)
Distances, perimeters and diameters 161(9)
Measures of shape 170(5)
Boundary statistics 175(7)
Summary 182(3)
Summary of Results 185(6)
Appendix 191(10)
A.1 Hardware 191(6)
A.1.1 The central processing unit 193(1)
A.1.2. The image capture device 194(1)
A.1.3 The framestore 195(1)
A.1.4 Image storage 195(1)
A.1.5 Display 196(1)
A.1.6 Printing 197(1)
A.2 Software 197(4)
A.2.1 Choosing software 198(1)
A.2.2 Software compatibility and image 199(2)
formats
References 201(8)
Author index 209(4)
Subject index 213