Abstract
In this chapter, the basic mathematic and algorithmic tools for the frequency-domain analysis of digital images are explained. Also introduced is the two-dimensional discrete-space convolution that is the basis for linear filtering. It also explores the concept of image frequency or, more generally, of two-dimensional frequency. An understanding of frequency domain and linear filtering concepts is essential to comprehend such significant topics as image and video enhancement, restoration, compression, segmentation, and wavelet-based methods. Exploring these ideas in a two-dimensional setting has the advantage that frequency domain concepts and transforms can be visualized as images, often enhancing the accessibility of ideas.
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