Book contents
Contents
- 1 Nonlinear Signal Processing
- 1.1 Signal Processing Model
- 1.2 Signal and Noise Models
- 1.3 Fundamental Problems in Noise Removal
- 1.4 Algorithms
- 2 Statistical Preliminaries
- 2.1 Random Variables and Distributions
- 2.2 Signal and Noise Models
- 2.3 Estimation
- 2.4 Some Useful Distributions
- 3 1001 Solutions
- 3.1 Trimmed Mean Filters
- 3.2 Other Trimmed Mean Filters
- 3.3 L-Filters
- 3.4 C-Filters
- 3.5 Weighted Median Filters
- 3.6 Ranked-Order and Weighted Order Statistic Filters
- 3.7 Multistage Median Filters
- 3.8 Median Hybrid Filters
- 3.9 Edge-Enhancing Selective Filters
- 3.10 Rank Selection Filters
- 3.11 M-Filters
- 3.12 R-Filters
- 3.13 Weighted Majority with Minimum Range Filters
- 3.14 Nonlinear Mean Filters
- 3.15 Stack Filters
- 3.16 Generalizations of Stack Filters
- 3.17 Morphological Filters
- 3.18 Soft Morphological Filters
- 3.19 Polynomial Filters
- 3.20 Data-Dependent Filters
- 3.21 Decision-Based Filters
- 3.22 Iterative, Cascaded, and Recursive Filters
- 3.23 Some Numerical Measures of Nonlinear Filters
- 3.24 Discussion
- 4 Statistical Analysis and Optimization of Nonlinear Filters
- 4.1 Methods Based on Order Statistics
- 4.2 Stack Filters
- 4.2.1 Output Distribution of a Stack Filter
- 4.2.2 Joint Distribution of Two Stack Filters
- 4.2.3 Output Moments of a Stack Filter
- 4.2.4 Rank Selection Probabilities of Stack Filters
- 4.2.5 Optimization of Stack Filters
- 4.2.6 Stack Filter Optimization in the Boolean Lattice
- 4.3 Multistage and Hybrid Filters
- 4.4 Discussion
- 5 Exercises
- Bibliography
- Index
Esa Alhoniemi
Last modified: Fri Sep 19 11:15:42 DST 1997