![]() Using an image editor and lossy compression, you might create a compressed version of that photo that is 200KB. For example, a photo in its raw form may take 5MB, but if you want to use it on a web page, using that photo would cause the page to load more slowly. Files relying upon human perception often utilize lossy compression, since the source material may have more resolution than we can realistically perceive. Lossy compression can often produce more compact results by discarding data that may not affect the final resolution of the file. Documents, spreadsheets, and similar other files are often compressed with lossless techniques like these LZ-based algorithms. The larger the string it can find, and the more often that string recurs through the file, the more it can compress the output file. The algorithm uses an adaptive technique that analyzes the source file for strings of characters that repeat. Most lossless compression algorithms build upon the work Abraham Lempel and Jacov Ziv pioneered in the late 1970s in creating the algorithms that would be called LZ (many subsequent compression algorithms build upon this work, so their names begin with this pattern: LZO, LZW, LSWL, LZX, LZJB, etc.). A lossless compressed file retains all information so that decompressing it restores the original file in its entirety. Compressing them further yields results only a few percent smaller than the originals–in some cases, they may become slightly larger when compressed, since the compression can add a small amount of management data to the file.Ĭompression comes in two basic types, lossless and lossy. ![]() Conversely, files that have already been compressed, such as MP3s and JPEGs, have low redundancy. Text files, for example, may have many repeated words or letter combinations that can produce significant compression–as much as 80%, in some cases.ĭatabases and spreadsheets often also make good candidates for file compression because they, too, typically have repeated content. ![]() The more redundancy the compression algorithm detects, the smaller the compressed file becomes. Most compression techniques work by reducing the space redundant information in a file takes up. This technology has applications ranging from archives and backups to media and software distribution. ![]() While the type of source file and the type of compression algorithm determines how well compression works, a compressed set of an average mix of files typically takes about 50 percent less space than the originals. Many different kinds of software, including backup programs, operating systems, media apps, and file management utilities, use this technique. Run the following command to create one.This article is good for general audiences and provides an introduction to data compression techniques and uses.įile compression is a technique for “squeezing” data files so that they take up less storage space, whether on a hard drive or other media. Assuming that your system already has these tools installed, let’s get started.Īt first, we need a test file. As for the “zip” compression, we’ll be using the zip tool. Majority of the compression methods are available from the tool tar. The compression methods I’ll discuss in this article are all lossless compression methods. Using a “lossless” compression method, the original file can be reconstructed from the compressed file. Lossless compression: This is the most widely used type of compression.When an MP3 is created from the original audio file, it’s significantly smaller than the original source music file. Essentially, once compressed, there’s a risk that the original file can’t be reconstructed using the compressed archive.Ī solid example of this type of compression is the well-known MP3 format. Lossy compression: This is a risky type of compression that doesn’t guarantee data integrity.Because of how different compression works and the random nature of files, the mileage may vary greatly. In the case of file compression, a compression method utilizes its own algorithm and mathematical calculation to generate an output that’s generally less than the size of the original file. Compression typesĬompression is encoding and representing information using fewer bits than it originally was. In the case of Linux, there are various compression options, each with its own benefits.Ī generic Linux distro offers access to a handful of really useful and simple compression mechanisms. Compression, in general, is a useful method that is essentially encoding information using less data than the original one.
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