What will We Learn?
- What is neighborhood processing and how does it differ from point processing?
- What is convolution and how is it used to process digital images?
- What is a low-pass linear filter, what is it used for, and how can it be implemented using 2D convolution?
- What is a median filter and what is it used for?
- What is a high-pass linear filter, what is it used for, and how can it be implemented using 2D convolution?
10.1 Neighborhood Processing
The underlying theme throughout this chapter is the use of neighborhood-oriented operations for image enhancement. The basics of neighborhood processing were introduced in Section 2.4.2. We call neighborhood-oriented operations those image processing techniques in which the resulting value for a pixel at coordinates —which we shall call the reference pixel—is a function of the original pixel value at that point as well as the original pixel value of some of its neighbors. The way by which the neighboring values and the reference pixel value are combined to produce the result can vary significantly among different algorithms. Many algorithms work in a linear way and use 2D convolution (which essentially consists of sums of products, see Section 10.2), while others process the input values in a nonlinear way.
Regardless of the type (linear or nonlinear), neighborhood processing operations follow ...