 directed to read the tutorial information that can be found at www.dcs.ed.ac.uk/home/mxr/gfx/2d/JPEG.txt However, a high-level description of the process follows. Earlier, we discussed the fact that a 640x480-pixel image requires nearly a full megabyte of disk space for uncompressed storage. To reduce that requirement, JPEG performs a mathematical permutation of the image that removes redundant information contained in the image, thus reducing storage requirements for the image. This results in loss of infor- mation and, while this appears to be a bad thing, it really isn't because of the limitations of the human eye described earlier. Consider the image of my son Steve shown in Figure 2-20. Using a high-quality digital still camera, I took this portrait of him. I then Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright © 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website. Protocols Chapter 2 enlarged a small section of the image to illustrate how the JPEG com- pression algorithm actually works. Keep in mind that a digital image comprises a large number of individual pixels, each of which has indi- vidual color characteristics associated with it. In the original photo- graph, Steve's skin tones are relatively uniform across his face except for the areas that are in shadow, such as his eyes and parts of his chin. How- ever, when we enlarge a small area of the image, the pixels vary widely in terms of their color components. This disparity is what JPEG exploits as a way of getting the job done. It knows that the human eye cannot see the difference between these pixels until they are dramatically enlarged, as I have done in Figure 2-21. What JPEG does is cluster the pixels in 16-by-16-pixel groups. It then mathematically removes every other pixel, resulting in eight-by-eight- pixel arrays. It then performs a mathematical transformation of the 64- pixel arrays called a discrete cosine transform that c