We define a signal as data that measures either time-varying or spatially varying phenomena. Sound or electrocardiograms are excellent examples of time-varying quantities, while images embody the quintessential spatially varying cases. Moving images (movies or videos) are treated with the techniques of both types of signals, obviously.

The field of signal processing treats four aspects of this kind of data – its acquisition, quality improvement, compression, and feature extraction. SciPy has many routines to treat tasks effectively in any of the four fields. All these are included in two low-level modules (scipy.signal being the main one, with an emphasis in time-varying data, and scipy.ndimage, for images). Many of the routines in these two modules are based on Discrete Fourier Transform of the data.

In this chapter, we will cover the following things: