TITLE: Computer Imaging: Digital Image Analysis and Processing

AUTHOR: Scott E Umbaugh

PUBLISHER: CRC Press

DATE: September 26, 2007

 

TABLE OF CONTENTS

 

Dedication

Preface

Author Biography

Acknowledgements

 

SECTION I.   INTRODUCTION TO COMPUTER IMAGING

 

     CHAPTER 1. Computer Imaging

            1.1 Overview

1.2 Image Analysis and Computer Vision

            1.3 Image Processing.

            1.4 Key Points

            1.5 References and Further Reading

            1.6 Exercises

 

    CHAPTER 2. Computer Imaging Systems

2.1 Imaging Systems Overview

2.2 Image Formation and Sensing

                        1. Visible Light Imaging

                        2. Imaging Outside the Visible Range of the Electromagnetic Spectrum

                        3. Acoustic Imaging

                        4. Electron Imaging

                        5. Laser Imaging

                        6. Computer Generated Images

            2.3 The CVIPtools Software

                        1. Main Window

2. Image Viewer

3. Analysis Window

4. Enhancement Window

5. Restoration Window

6. Compression Window

7. Utilities Window

8. Help Window

2.4 Image Representation

1. Binary Images

2. Gray-Scale Images

3. Color Images

4. Multispectral Images

5. Digital Image File Formats

            2.5 Key Points

            2.6 References and Further Reading

            2.7 Exercises

 

SECTION II.  DIGITAL IMAGE ANALYSIS

 

     CHAPTER 3. Introduction to Digital Image Analysis

3.1 Introduction

                        1. Overview

                        2. System Model

3.2 Preprocessing

                        1. Region of Interest Geometry

                        2. Arithmetic and Logic Operations

                        3. Spatial Filters

                        4. Image Quantization

            3.3 Binary Image Analysis

                        1. Thresholding via Histogram

2. Connectivity and Labeling

3. Basic Binary Object Features

4. Binary Object Classification

3.4 Key Points

            3.5 References and Further Reading

3.6 Exercises

 

    CHAPTER 4.  Segmentation and Edge/Line Detection

            4.1 Introduction and Overview

4.2 Edge/Line Detection

                        1. Gradient Operators

                        2. Compass Masks

                        3. Advanced Edge Detectors

                        4. Edges in Color Images

                        5. Edge Detector Performance

                        6. Hough Transform

                                    1. CVIPtools Parameters for the Hough Transform

4.3 Segmentation

                        1. Region Growing and Shrinking

2. Clustering Techniques

                        3. Boundary Detection

                        4. Combined Segmentation Approaches

5. Morphological Filtering

4.4 Key Points

            4.5 References and Further Reading

4.6 Exercises

 

     CHAPTER 5. Discrete Transforms

5.1 Introduction and Overview

5.2 Fourier Transform

1. The One-Dimensional Discrete Fourier Transform

                        2. The Two-Dimensional Discrete Fourier Transform

                        3. Fourier Transform Properties

                                    1. Linearity

                                    2. Convolution

                                    3. Translation

                                    4. Modulation

                                    5. Rotation

                                    6. Periodicity

                        4. Displaying the Fourier Transform

            5.3. Cosine Transform

            5.4. Walsh-Hadamard Transform

            5.5. Haar Transform

            5.6 Principal Components Transform

5.7 Filtering

                        1. Lowpass Filters

                        2. Highpass Filters

                        3. Bandpass and Bandreject Filters

5.8 Wavelet Transform

5.9 Key Points

            5.10 References and Further Reading

5.11 Exercises

 

     CHAPTER 6. Feature Analysis and Pattern Classification

6.1 Introduction and Overview

6.2 Feature Extraction

                        1. Shape Features

2. Histogram Features

3. Color Features

4. Spectral Features

                        5. Texture Features

                        6. Feature Extraction with CVIPtools

            6.3 Feature Analysis

                        1. Feature Vectors and Feature Spaces

                        2. Distance and Similarity Measures

                        3. Data Preprocessing

6.4 Pattern Classification

                        1. Algorithm Development: Training and Testing Methods

                        2. Classification Algorithms and Methods

6.5 Key Points

            6.6 References and Further Reading

6.7 Exercises

 

SECTION III. DIGITAL IMAGE PROCESSING

 

    CHAPTER 7. Digital Image Processing and Visual Perception

7.1 Introduction and Overview

7.2 Human Visual Perception

1. The Human Visual System

2. Spatial Frequency Resolution

3. Brightness Adaptation

4. Temporal Resolution

5. Perception and Illusion

            7.3 Image Fidelity Criteria

                        1. Objective Fidelity Measures

                        2. Subjective Fidelity Measures

7.4 Key Points

            7.5 References and Further Reading

7.6 Exercises

 

     CHAPTER 8. Image Enhancement

8.1  Introduction and Overview

8.2 Gray-Scale Modification

            1. Mapping Equations

2. Histogram Modification

3. Adaptive Contrast Enhancement

4. Color 

8.3 Image Sharpening:

            1. Highpass Filtering

            2. High Frequency Emphasis

            3. Directional Difference Filters

            4. Homomorphic Filtering

            5. Unsharp Masking

            6. Edge Detector-Based Sharpening Algorithms

8.4 Image Smoothing:

            1. Frequency Domain Lowpass Filtering

            2. Convolution Mask Lowpass Filtering

            3. Median Filtering

8.5 Key Points

            8.6 References and Further Reading

8.7 Exercises

 

     CHAPTER 9. Image Restoration

9.1 Introduction and Overview

1. System Model

            9.2 Noise Models

                        1. Noise Histograms

                        2. Periodic Noise

                        3. Estimation of Noise

9.3 Noise Removal Using Spatial Filters

1. Order Filters

2. Mean Filters

3. Adaptive Filters

            9.4 The Degradation Function

                        1. The Spatial Domain – The Point Spread Function

                        2. The Frequency Domain – The Modulation/Optical Transfer Function

                        3 Estimation of the Degradation Function

9.5 Frequency Domain Restoration Filters

            1. Inverse Filter

            2. Wiener Filter

            3. Constrained Least Squares Filter

            4. Geometric Mean Filters

            5. Adaptive Filtering

            6. Bandpass, Bandreject and Notch Filters

            7. Practical Considerations

9.6 Geometric Transforms

1. Spatial Transforms

2. Gray-Level Interpolation

3. The Geometric Restoration Procedure

4. Geometric Restoration with CVIPtools

9.7 Key Points

            9.8 References and Further Reading

9.9 Exercises

 

     CHAPTER 10. Image Compression       

10.1 Introduction and Overview

            1. Compression System Model

10.2 Lossless Compression Methods

                        1. Huffman Coding

                        2. Run-length Coding

                        3. Lempel-Ziv-Welch Coding

                        4. Arithmetic Coding    

10.3 Lossy Compression Methods

                        1. Gray-Level Run-Length Coding

                        2. Block Truncation Coding

                        3. Vector Quantization

                        4. Differential Predictive Coding

                        5. Model-Based and Fractal Compression

6. Transform Coding

                        7. Hybrid and Wavelet Methods

            10.4 Key Points

            10.5 References and Further Reading

10.6 Exercises

 

SECTION IV. PROGRAMMING WITH CVIPTOOLS

 

     CHAPTER 11. CVIPlab

11.1 Introduction to CVIPlab

11.2 Toolkits, Toolbox and Application Libraries

11.3 Compiling and Linking CVIPlab

            1. How to Build the CVIPlab Project with Micorsoft’s Visual C++ 6.0

            2. The Mechanics of Adding a Function with Microsoft’s Visual C++ 6.0

            3. Using CVIPlab in the Programming Exercises

11.4 Image Data and File Structures

11.5 CVIP Projects

            1. Computer Vision Projects

            2. Digital Image Processing Projects

 

      CHAPTER 12. CVIPtools C Function Libraries

            12.1 Introduction and Overview

12.2 Arithmetic and Logic Library – ArithLogic.lib

12.3 Band Image Library – Band.lib

12.4 Color Image Library – Color.lib

12.5 Compression Library – Compression.lib

12.6 Conversion Library – Conversion.lib

            12.7 Display Library – Display.lib

12.8 Feature Extraction Library – Feature.lib

12.9 Geometry Library – Geometry.lib

12.10 Histogram Library – Histogram.lib

12.11 Image Library – Image.lib

12.13 Data Mapping Library – Mapping.lib

12.14 Morphological Library – Morphological.lib

12.15 Noise Library – Noise.lib

12.16 Segmentation Library – Segmentation.lib

12.17 Spatial Filter Library – SpatialFilter.lib

12.18 Transform Library – Transform.lib

12.19 Transform Filter Library – TransformFilter.lib

 

SECTION V. APPENDICES

 

A. The CVIPtools CD-ROM

B. Installing and Updating CVIPtools

C. CVIPtools C functions

D. CVIP Resources

            E. CVIPtools Software Organization

F. Common Object Module (COM) Functions – cviptools.dll