8.1. Introduction

This chapter presents several digital filtering techniques applied to two dimensional data. The most common applications are concerned with the processing of images. Other kinds of data can be processed using similar techniques, such as time-frequency representations and time-scale representations of mono-dimensional signals.

The fundamental principles of this kind of filtering are based on the 2-D sampling theorem and on the Fourier transform.

This chapter includes a brief reminder of continuous models and stationary 2-D linear filtering, since most of the later explanations make use of these. Then, we will introduce two-dimensional sampling techniques. Filtering operations will then be discussed in both spatial and frequency domains.

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