If a typical message were statistically analyzed, it would be found that certain characters are used much more frequently than others. By analyzing a message before it is transmitted, short binary codes may be assigned to frequently used characters and longer codes to rarely used characters. In doing so, it is possible to reduce the total number of characters sent without altering the information in the message. Appropriate decoding at the receiver will restore the message to its original form. This procedure, known as data compression, may result in a 50 percent or greater savings in the amount of data transmitted. Even though time is necessary to analyze the message before it is transmitted, the savings may be great enough so that the total time for compression, transmission, and decompression will still be lower than it would be when sending an uncompressed message.
Some kinds of data will compress much more than others. Data that represents images, for example, will usually compress significantly, perhaps by as much as 80 percent over its original size. Data representing a computer program, on the other hand, may be reduced only by 15 or 20 percent.
A compression method called Huffman coding is frequently used in data communications, and particularly in fax transmission. Clearly, most of the image data for a typical business letter represents white paper, and only about 5 percent of the surface represents black ink. It is possible to send a single code that, for example, represents a consecutive string of 1000 white pixels rather than a separate code for each white pixel. Consequently, data compression will significantly reduce the total message length for a faxed business letter. Were the letter made up of randomly distributed black ink covering 50 percent of the white paper surface, data compression would hold no advantages.