Digital image processing /

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Bibliographic Details
Author / Creator:	Jähne, Bernd, 1953-
Edition:	5th rev. and extended ed.
Imprint:	Berlin ; New York : Springer, c2002.
Description:	xii, 585 p. ; 24 cm. + 1 computer optical disk (4 3/4 in.)
Language:	English
Subject:	Image processing -- Digital techniques. Image processing -- Digital techniques.
Format:	Print Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/4721395

Hidden Bibliographic Details
ISBN:	3540677542

Table of Contents:

I. Foundation
1. Applications and Tools
1.1. A Tool for Science and Technique
1.2. Examples of Applications
1.3. Hierarchy of Image Processing Operations
1.4. Image Processing and Computer Graphics
1.5. Cross-disciplinary Nature of Image Processing
1.6. Human and Computer Vision
1.7. Components of an Image Processing System
1.8. Further Readings ç
2. Image Representation
2.1. Introduction
2.2. Spatial Representation of Digital Images
2.3. Wave Number Space and Fourier Transform
2.4. Discrete Unitary Transforms ç
2.5. Fast Algorithms for Unitary Transforms
2.6. Further Readings ç
3. Random Variables and Fields
3.1. Introduction
3.2. Random Variables
3.3. Multiple Random Variables
3.4. Probability Density Functions
3.5. Stochastic Processes and Random Fields ç
3.6. Further Readings ç
4. Neighborhood Operations
4.1. Basic Properties and Purpose
4.2. Linear Shift-Invariant Filters å
4.3. Recursive Filters ç
4.4. Rank Value Filtering
4.5. Further Readings ç
5. Multiscale Representation
5.1. Scale
5.2. Scale Space å
5.3. Multigrid Representations
5.4. Further Readings ç
II. Image Formation and Preprocessing
6. Quantitative Visualization
6.1. Introduction
6.2. Waves and Particles
6.3. Radiometry, Photometry, Spectroscopy, and Color
6.4. Interactions of Radiation with Matter ç
6.5. Further Readings ç
7. Image Formation
7.1. Introduction
7.2. World and Camera Coordinates
7.3. Ideal Imaging: Perspective Projection å
7.4. Real Imaging
7.5. Radiometry of Imaging
7.6. Linear System Theory of Imaging å
7.7. Further Readings ç
8. 3-D Imaging
8.1. Basics
8.2. Depth from Triangulation
8.3. Depth from Time-of-Flight
8.4. Depth from Phase: Interferometry
8.5. Shape from Shading å
8.6. Depth from Multiple Projections: Tomography
8.7. Further Readings ç
9. Digitization, Sampling, Quantization
9.1. Definition and Effects of Digitization
9.2. Image Formation, Sampling, Windowing
9.3. Reconstruction from Samples å
9.4. Quantization
9.5. Further Readings ç
10. Pixel Processing
10.1. Introduction
10.2. Homogeneous Point Operations
10.3. Inhomogeneous Point Operations å
10.4. Multichannel Point Operations ç
10.5. Geometric Transformations
10.6. Interpolation å
10.7. Further Readings ç
III. Feature Extraction
11. Averaging
11.1. Introduction
11.2. General Properties of Averaging Filters
11.3. Box Filter
11.4. Binomial Filter
11.5. Filters as Networks ç
11.6. Efficient Large-Scale Averaging ç
11.7. Nonlinear Averaging
11.8. Averaging in Multichannel Images ç
11.9. Further Readings ç
12. Edges
12.1. Introduction
12.2. General Properties of Edge Filters
12.3. Gradient-Based Edge Detection å
12.4. Edge Detection by Zero Crossings
12.5. Regularized Edge Detection
12.6. Edges in Multichannel Images ç
12.7. Further Readings ç
13. Simple Neighborhoods
13.1. Introduction
13.2. Properties of Simple Neighborhoods
13.3. First-Order Tensor Representation å
13.4. Local Wave Number and Phase ç
13.5. Tensor Representation by Quadrature Filter Sets ç
13.6. Further Readings ç
14. Motion
14.1. Introduction
14.2. Basics
14.3. First-Order Differential Methods ç
14.4. Tensor Methods
14.5. Second-Order Differential Methods ç
14.6. Correlation Methods
14.7. Phase Method ç
14.8. Further Readings ç
15. Texture
15.1. Introduction
15.2. First-Order Statistics
15.3. Rotation and Scale Variant Texture Features
15.4. Further Readings ç
IV. Image Analysis
16. Segmentation
16.1. Introduction
16.2. Pixel-Based Segmentation
16.3. Edge-Based Segmentation
16.4. Region-Based Segmentation
16.5. Model-Based Segmentation
16.6. Further Readings ç
17. Regularization and Modeling
17.1. Unifying Local Analysis and Global Knowledge
17.2. Purpose and Limits of Models
17.3. Variational Image Modeling å
17.4. Controlling Smoothness
17.5. Diffusion Models
17.6. Discrete Inverse Problems å
17.7. Network Models ç
17.8. Inverse Filtering
17.9. Further Readings ç
18. Morphology
18.1. Introduction
18.2. Neighborhood Operations on Binary Images
18.3. General Properties
18.4. Composite Morphological Operators
18.5. Further Readings ç
19. Shape Presentation and Analysis
19.1. Introduction
19.2. Representation of Shape
19.3. Moment-Based Shape Features
19.4. Fourier Descriptors
19.5. Shape Parameters
19.6. Further Readings ç
20. Classification
20.1. Introduction
20.2. Feature Space
20.3. Simple Classification Techniques
20.4. Further Readings ç
V. Reference Part
A. Reference Material
B. Notation
Bibliography
Index

Digital image processing /

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