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Compressing Files
Throughout the history of computing, there has been a struggle to get the most data into the smallest available space, whether that space be memory, storage devices, or network bandwidth. Many of the data services that we take for granted today, such as portable mu- sic players, high definition television, or broadband Internet, owe their existence to effec- tive data compression techniques.
Data compression is the process of removing redundancy from data. Let’s consider an imaginary example. Say we had an entirely black picture file with the dimensions of 100 pixels by 100 pixels. In terms of data storage (assuming 24 bits, or 3 bytes per pixel), the image will occupy 30,000 bytes of storage:
100 * 100 * 3 = 30,000
An image that is all one color contains entirely redundant data. If we were clever, we could encode the data in such a way that we simply describe the fact that we have a block
of 10,000 black pixels. So, instead of storing a block of data containing 30,000 zeros (black is usually represented in image files as zero), we could compress the data into the number 10,000, followed by a zero to represent our data. Such a data compression scheme is called run-length encoding and is one of the most rudimentary compression techniques. Today’s techniques are much more advanced and complex but the basic goal remains the same — get rid of redundant data.
Compression algorithms (the mathematical techniques used to carry out the compression) fall into two general categories, lossless and lossy. Lossless compression preserves all the data contained in the original. This means that when a file is restored from a compressed version, the restored file is exactly the same as the original, uncompressed version. Lossy compression, on the other hand, removes data as the compression is performed, to allow more compression to be applied. When a lossy file is restored, it does not match the origi- nal version; rather, it is a close approximation. Examples of lossy compression are JPEG (for images) and MP3 (for music). In our discussion, we will look exclusively at lossless compression, since most data on computers cannot tolerate any data loss.