ABSTRACT
This chapter discusses the fundamentals of representing and visualizing different kinds of visual data like images, three dimensional (3D) surfaces and point clouds. It also discusses two alternate representations of data in the spatial/time domain and frequency domain. The chapter talks about practical issues involving noise in data and how it needs to be handled on a case by case basis. The simplest visualization of a multi-dimensional data is a traditional plot of the dependent variable with respect to the independent ones. The ideal visualization is an image where each spatial coordinate is visualized as a color which is also a 3D quantity. The chapter describes data representation in the context of visual computing— namely audio, images, videos and meshes. An analytical representation of data is in the form of a function of one or more independent variables. In a discrete representation, a geometric entity is represented as a collection of other geometric entities as opposed to an analytical equation.
