Nonlinear Image Processing (Communications, Networking and Multimedia)

✍ Scribed by Giovanni Sicuranza, Sanjit Mitra (editor)

• Publisher: Academic Press
• Year: 2000
• Tongue: English
• Leaves: 477
• Edition: 1
• Category: Library

✦ Synopsis

This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.

• Presents the latest developments in a variety of filter design techniques and algorithms
• Contains essential information for development of Human Vision Systems (HVS)
• Provides foundations for digital imaging and image capture technology

✦ Table of Contents

Nonlinear Image Processing
Copyright Page
Contents
Preface
Chapter 1. Analysis and Optimization of Weighted Order Statistic and Stack Filters
1.1 Introduction
1.2 Median and Order Statistic Filters
1.3 Stack Filters
1.4 Image Processing Applications
1.5 Summary
Chapter 2. Image Enhancement and Analysis with Weighted Medians
2.1 Introduction
2.2 Weighted Median Smoothers and Filters
2.3 Image Denoising
2.4 Image Zooming
2.5 Image Sharpening
2.6 Optimal Frequency Selection WM Filtering
2.7 Edge Detection
2.8 Conclusion
Chapter 3. Spatial–Rank Order Selection Filters
3.1 Introduction
3.2 Selection Filters and Spatial–Rank Ordering
3.3 Spatial-Rank Order Selection Filters
3.4 Optimization
3.5 Applications
3.6 Future Directions
Chapter 4. Signal-Dependent Rank-Ordered-Mean (SD-ROM) Filter
4.1 Introduction
4.2 Impulse Noise Model
4.3 Definitions
4.4 The SD-ROM Filter
4.5 Generalized SD-ROM Method
4.6 Experimental Results
4.7 Restoration of Images Corrupted by Streaks
4.8 Concluding Remarks
Chapter 5. Nonlinear Mean Filters and Their Applications in Image Filtering and Edge Detection
5.1 Introduction
5.2 Nonlinear Mean Filters
5.3 Signal-Dependent Noise Filtering by Nonlinear Means
5.4 Edge Detectors Based on Nonlinear Means
5.5 Grayscale Morphology Using £p Mean Filters
5.6 Ultrasonic Image Processing Using £2 Mean Filters
5.7 Sorting Networks Using £p Mean Comparators
5.8 Edge Preserving Filtering by Combining Nonlinear Means and Order Statistics
5.9 Summary
Chapter 6. Two-Dimensional Teager Filters
6.1 Introduction
6.2 Discrete Volterra Series and Properties
6.3 Interpretation of Frequency Responses
6.4 The Teager Algorithm and One-Dimensional Extensions
6.5 Spectrum of the Output Signal
6.6 Mean-Weighted Highpass Filters
6.7 Least-Squares Design of Edge Extracting Filters
6.8 Summary
6.9 Appendix
Chapter 7. Polynomial and Rational Operators for Image Processing and Analysis
7.1 Introduction
7.2 Theoretical Survey of Polynomial and Rational Filters
7.3 Applications of Polynomial Filters
7.4 Applications of Rational Filters
7.5 Conclusions and Remaining Issues
Chapter 8. Nonlinear Partial Differential Equations in Image Processing
8.1 Introduction
8.2 Segmentation of Scalar and Multivalued Images
8.3 Nonlinear PDEs in General Manifolds: Harmonic Maps and Direction Diffusion
Chapter 9. Region-Based Filtering of Images and Video Sequences: A Morphological Viewpoint
9.1 Introduction
9.2 Classical Filtering Approaches
9.3 Connected Operators
9.4 Connected Operators Based on Reconstruction Processes
9.5 Connected Operators Based on Region-Tree Pruning
9.6 Conclusions
Chapter 10. Differential Morphology
10.1 Introduction
10.2 2D Morphological Systems and Slope Transforms
10.3 PDEs for Morphological Image Analysis
10.4 Curve Evolution
10.5 Distance Transforms
10.6 Eikonal PDE and Distance Propagation
10.7 Conclusions
Chapter 11. Coordinate Logic Filters: Theory and Applications in Image Analysis
11.1 Introduction
11.2 Coordinate Logic Operations on Digital Signals
11.3 Derivation of the Coordinate Logic Filters
11.4 Properties of Coordinate Logic Filters
11.5 Morphological Filtering Using Coordinate Logic Operations on Quantized Images
11.6 Image Analysis and Pattern Recognition Applications
11.7 Concluding Remarks
Chapter 12. Nonlinear Filters Based on Fuzzy Models
12.1 Introduction
12.2 Fuzzy Models
12.3 Fuzzy Weighted Mean (FWM) Filters
12.4 FIRE Filters
12.5 Evolutionary Neural Fuzzy Filters: A Case Study
12.6 Concluding Remarks and Future Trends
Chapter 13. Digital Halftoning
13.1 Introduction
13.2 Halftone Statistics
13.3 Blue-Noise Dithering
13.4 Green-Noise Dithering
13.5 Conclusions
Chapter 14. Intrinsic Dimensionality: Nonlinear Image Operators and Higher-Order Statistics
14.1 Introduction
14.2 Transdisciplinary Relevance of Intrinsic Dimensionality
14.3 i2D-Selective Nonlinear Operators
14.4 Frequency Design Methods for i2D Operators
14.5 i2D Operators and Higher-Order Statistics
14.6 Discussion
Index
Color Plate Section