Chapter 4. Image Transformation

Summary

Two-dimensional image transforms are extremely important areas of studies in image processing . The image output in the transformed space may be analyzed, interpreted and further processed for implementing diverse image processing tasks. These transformations are widely used, since by using these transformations, it is possible to express an image as a combination of a set of basic signals, known as the basis functions. Interestingly the human vision system which is a biological system, essentially performs the frequency analysis of the image incident on the retina of our eyes. Image transforms, such as Fourier Transform, reveal spectral structures embedded in images that may be used to characterize the image, as an example. In this chapter, we have introduced the principles of image transforms and elaborated on some of the popular and widely used image transformation techniques such as Fourier Transform, Discrete Cosine Transform, Walsh-Hadamard Transform, Karhaunen-Loeve (KL)Transform, etc. We also presented some visual examples.