Filtering is one of the fundamental tasks in signal and image processing. It is a process aimed at selectively extracting certain aspects of an image that are considered to convey important information in the context of a given application. Filtering removes noise in images, extracts interesting visual features, allows image resampling, and so on. It finds its roots in the general Signals and Systems theory. We will not cover this theory in detail here. However, this chapter will present some of the important concepts related to filtering and will show you how filters can be used in image-processing applications. But first, let's begin with a brief explanation of the concept of frequency domain analysis.

When we look at an image, we observe how the different gray-levels (or colors) are distributed over the image. Images differ from each other because they have a different gray-level distribution. However, there exists another point of view under which an image can be analyzed...