The previous chapters have discussed the various tools and properties that are used to characterize a digital image. The image begins as a reflective or radiant source; a distribution of energy is sensed by a device in one or several bands; the sensed signal is converted from analog to digital format and stored using a finite number of bits. The characteristics of an image include properties that are inherent to the content of the image, to the source of the energy distribution and to the sampling and quantization of the image.

The characteristics can be deterministic, such as the size of the image, or stochastic, as in the case of the signal-to-noise ratio in a recorded image. In this chapter, we will consider the various characterizations and their effect on the processing of the image. The characteristics of an image or class of images are important to determine the optimal recording, display, coding and processing. In general, if we are concerned with a specific image, the characteristics are deterministic, since they can be determined by measurements on the image. Such parameters as the mean, minimum and maximum values are examples. If we are concerned with a class of images, it is reasonable to treat the class as a statistical ensemble and characterize it by statistical parameters. Mean, minimum and maximum are examples, but in this case the values are interpreted differently.