This text provides insight into the design of optimal image processing operators for implementation directly into digital hardware. Starting with simple restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications. The text is aimed principally at electronics engineers and computer scientists, but will also be of interest to anyone working with digital images.
Contents
- Acknowledgments
- Introduction
- What Is a Logic-Based Filter?
- How Accurate Is the Logic-Based Filter?
- How Do You Train the Filter for a Task
- Increasing Filters and Mathematical Morphology
- The Median Filter and Its Variants
- Extension to Grayscale
- Grayscale Implementation
- Case Study: Noise Removal from Astronomical Images
- Conclusions
- Index
