of course, lossless compression algorithms; JPEG, however, achieves more efficient com- pression than is possible with competing lossless techniques. On first blush this would appear to be a problem for many applications, since the compression process actually "squeezes" information out of the original image, leaving a slightly inferior artifact. For example, a diagnostician examining a medical image might be concerned with the fact that the compressed image is not as good as the original. Luckily, this is not a problem for one very simple reason: The human eye is an imperfect view- ing device. JPEG is designed to take advantage of well-understood limi- tations in the human eye, particularly the fact that small color changes are not perceived as discretely as small brightness changes. Clearly, JPEG is designed to compress images that will be viewed by people and, therefore, do not have to be absolutely faithful reproductions of the orig- inal image from which they were created. A machine analysis of a JPEG 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 image would certainly yield inferior results, but to the human eye it is perfectly acceptable. Of course, the degree of loss that occurs during a JPEG transforma- tion can be controlled by adjusting a variety of compression parameters relative to each other. For example, file size and image quality can be adjusted relative to one another. A medical image, which requires extremely high quality on the image output side, would require a large file size, while a compressed text document could easily suffer significant loss without losing readability, resulting in a very small file. The hardware or software coders that create (compress) and expand (decompress) JPEG images are called CODECs. If high image quality is not critically important, a low cost, higher loss CODEC can be 