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In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content.
A compression artifact (or artefact) is a noticeable distortion of media (including images, audio, and video) caused by the application of lossy compression. Lossy data compression involves discarding some of the media's data so that it becomes small enough to be stored within the desired disk space or transmitted (streamed) within the ...
Lossy image compression is used in digital cameras, to increase storage capacities. Similarly, DVDs, Blu-ray and streaming video use lossy video coding formats. Lossy compression is extensively used in video. In lossy audio compression, methods of psychoacoustics are used to remove non-audible (or less audible) components of the audio signal.
Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...
Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal number of bits per symbol, as measured by the rate R, that should be communicated over a channel, so that the source (input signal) can be approximately reconstructed at the receiver (output signal) without ...
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
In data compression and psychoacoustics, transparency is the result of lossy data compression accurate enough that the compressed result is perceptually indistinguishable from the uncompressed input, i.e. perceptually lossless. A transparency threshold is a given value at which transparency is reached. It is commonly used to describe compressed ...
In 1973, David Slepian and Jack Keil Wolf proposed the information theoretical lossless compression bound on distributed compression of two correlated i.i.d. sources X and Y. [3] After that, this bound was extended to cases with more than two sources by Thomas M. Cover in 1975, [4] while the theoretical results in the lossy compression case are presented by Aaron D. Wyner and Jacob Ziv in 1976.