ABSTRACT
The development of image analysis libraries has expanded the ability to construct short scripts that perform complicated tasks. Thus, the amount of real estate in publications required to precisely describe the algorithm is often much larger than the space required to write the computer script. An image is usually conceived as a two-dimensional array of pixel values. However, the number of dimensions increases with the inclusion of color, motion, or more spatial dimensions. Images are manipulated through the application of operators which are organized into several categories. The chapter presents a few of these operators to demonstrate how the notation functions. The operator categories are as follows: creation operators, channel operators, information operators, intensity operators, geometric operators, transformation operators and expansion operators. The transformation operators create a new image or matrix representing the data in a very different coordinate system. The most popular of these is a Fourier transform which converts data from an image space to a frequency space.
