ABSTRACT
This chapter begins by summarizing sampling and reconstruction using the concrete one-dimensional example of digital audio. It presents the basic mathematics and algorithms that underlie sampling and reconstruction in one and two dimensions. The chapter details the frequency-domain viewpoint, which provides many insights into the behavior of these algorithms. It discusses the sampling, filtering, and reconstruction in the abstract so far, using mostly 1D signals for examples. The chapter observes the most important and most common application of signal processing in graphics is for sampled images. This electrical signal needs to be stored somehow so that it may be played back at a later time and sent to a loudspeaker that converts the voltage back into pressure waves by moving a diaphragm in synchronization with the voltage. The purpose of using a reconstruction filter different from the box filter is to more completely eliminate the alias spectra, reducing the leakage of high-frequency artifacts into the reconstructed signal.
