Multimedia compression can be thought of as a war against unnecessary noise. Noise is the unwanted random dot pattern overlaid on videos and graphics when electronic noise is present, due in part to the random motion of electrons. Noise creeps into images, both still and motion, with the more lossy steps you take when manipulating images. These random dot patterns, or “snow,” prevent compression algorithms from working optimally, increasing file sizes. By minimizing the noise in your original images and videos, you can gain the maximum amount of compression when optimizing images and videos destined for the Web.
While streaming-media files make up only a small portion of the total web objects on the average web page, less than 1.3% according to Levering & Cutler (2006), a small fraction of streaming media is responsible for nearly half of the streaming media traffic (Chesire et a. 2001). In fact, YouTube is responsible for about 10% of all traffic on the Internet (Nowak 2007) and is growing at over 162% a year (see Table 1). Consequently the optimization of streaming media, movies in particular, is important to minimize load times, reduce bandwidth bills, and maximize web page speed.