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crete cosine transform dct it was first proposed in 1972 by nasir ahmed who then developed a working algorithm with t natarajan and k r rao in 1973 before introducing it in january 1974 15 16 dct is the most widely used lossy compression method and is used in multimedia formats for images such as jpeg and heif 17 video such as mpeg avc and hevc and audio such as mp3 aac and vorbis 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 compression of human speech is often performed with even more specialized techniques speech coding is distinguished as a separate discipline from general purpose audio compression speech coding is used in internet telephony for example audio compression is used for cd ripping and is decoded by the audio players citation needed lossy compression can cause generation loss theory edit the theoretical basis for compression is provided by information theory and more specifically shannon s source coding theorem domain specific theories include algorithmic information theory for lossless compression and rate distortion theory for lossy compression these areas of study were essentially created by claude shannon who published fundamental papers on the topic in the late 1940s and early 1950s other topics associated with compression include coding theory and statistical inference 18 machine learning edit there is a close connection between machine learning and compression a system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression by using arithmetic coding on the output distribution conversely an optimal compressor can be used for prediction by finding the symbol that compresses best given the previous history this equivalence has been used as a justification for using data compression as a benchmark for general intelligence 19 20 21 an alternative view can show compression algorithms implicitly map strings into implicit feature space vectors and compression based similarity measures compute similarity within these feature spaces for each compressor c we define an associated vector space ℵ such that c maps an input string x corresponding to the vector norm x an exhaustive examination of the feature spaces underlying all compression algorithms is precluded by space instead feature vectors chooses to examine three representative lossless compression methods lzw lz77 and ppm 22 according to aixi theory a connection more directly explained in hutter prize the best possible compression of x is the smallest possible software that generates x for example in that model a zip file s compressed size includes both the zip file and the unzipping software since you can not unzip it without both but there may be an even smaller combined form examples of ai powered audio video compression software include nvidia maxine aivc 23 examples of software that can perform ai powered image compression include opencv tensorflow matlab s image processing toolbox ipt and high fidelity generative image compression 24 in unsupervised machine learning k means clustering can be utilized to compress data by grouping similar data points into clusters this technique simplifies handling extensive datasets that lack predefined labels and finds widespread use in fields such as image compression 25 data compression aims to reduce the size of data files enhancing storage efficiency and speeding up data transmission k means clustering an unsupervised machine learning algorithm is employed to partition a dataset into a specified number of clusters k each represented by the centroid of its points this process condenses extensive datasets into a more compact set of representative points particularly beneficial in image and signal processing k means clustering aids in data reduction by replacing groups of data points with their centroids thereby preserving the core information of the original data while significantly decreasing the required storage space 26 large language models llms are also efficient lossless data compressors on some data sets as demonstrated by deepmind s research with the chinchilla 70b model developed by deepmind chinchilla 70b effectively compressed data outperforming conventional methods such as portable network graphics png for images and free lossless audio codec flac for audio it achieved compression of image and audio data to 43 4 and 16 4 of their original sizes respectively there is however some reason to be concerned that the data set used for testing overlaps the llm training data set making it possible that the chinchilla 70b model is only an efficient compression tool on data it has already been trained on 27 28 data differencing edit comparison of two revisions of a file data compression can be viewed as a special case of data differencing 29 30 data differencing consists of producing a difference given a source and a target with patching reproducing the target given a source and a difference since there is no separate source and target in data compression one can consider data compression as data differencing with empty source data the compressed file corresponding to a difference from nothing this is the same as considering absolute entropy corresponding to data compression as a special case of relative entropy corresponding to data differencing with no initial data the term differential compression is used to emphasize the data differencing connection uses edit image edit main article image compression entropy coding originated in the 1940s with the introduction of shannon fano coding 31 the basis for huffman coding which was developed in 1950 32 transform coding dates back to the late 1960s with the introduction of fast fourier transform fft coding in 1968 and the hadamard transform in 1969 33 an important image compression technique is the discrete cosine transform dct a technique developed in the early 1970s 15 dct is the basis for jpeg a lossy compression format which was introduced by the joint photographic experts group jpeg in 1992 34 jpeg greatly reduces the amount of data required to represent an image at the cost of a relatively small reduction in image quality and has become the most widely used image file format 35 36 its highly efficient dct based compression algorithm was largely responsible for the wide proliferation of digital images and digital photos 37 lempel ziv welch lzw is a lossless compression algorithm developed in 1984 it is used in the gif format introduced in 1987 38 deflate a lossless compression algorithm specified in 1996 is used in the portable network graphics png format 39 wavelet compression the use of wavelets in image compression began after the development of dct coding 40 the jpeg 2000 standard was introduced in 2000 41 in contrast to the dct algorithm used by the original jpeg format jpeg 2000 instead uses discrete wavelet transform dwt algorithms 42 43 44 jpeg 2000 technology which includes the motion jpeg 2000 extension was selected as the video coding standard for digital cinema in 2004 45 audio edit see also audio coding format and audio codec audio data compression not to be confused with dynamic range compression has the potential to reduce the transmission bandwidth and storage requirements of audio data audio compression formats compression algorithms are implemented in software as audio codecs in both lossy and lossless compression information redundancy is reduced using methods such as coding quantization dct and linear prediction to reduce the amount of information used to represent the uncompressed data lossy audio compression algorithms provide higher compression and are used in numerous audio applications including vorbis and mp3 these algorithms almost all rely on psychoacoustics to eliminate or reduce fidelity of less audible sounds thereby reducing the space required to store or transmit them 2 46 the acceptable trade off between loss of audio quality and transmission or storage size depends upon the application for example one 640 mb compact disc cd holds approximately one hour of uncompressed high fidelity music less than 2 hours of music compressed losslessly or 7 hours of music compressed in the mp3 format at a medium bit rate a digital sound recorder can typically store around 200 hours of clearly intelligible speech in 640 mb 47 lossless audio compression produces a representation of digital data that can be decoded to an exact digital duplicate of the original compression ratios are around 50 60 of the original size 48 which is similar to those for generic lossless data compression lossless codecs use curve fitting or linear prediction as a basis for estimating the signal parameters describing the estimation and the difference between the estimation and the actual signal are coded separately 49 a number of lossless audio compression formats exist see list of lossless codecs for a listing some formats are associated with a distinct system such as direct stream transfer used in super audio cd and meridian lossless packing used in dvd audio dolby truehd blu ray and hd dvd some audio file formats feature a combination of a lossy format and a lossless correction this allows stripping the correction to easily obtain a lossy file such formats include mpeg 4 sls scalable to lossless wavpack and optimfrog dualstream when audio files are to be processed either by further compression or for editing it is desirable to work from an unchanged original uncompressed or losslessly compressed processing of a lossily compressed file for some purpose usually produces a final result inferior to the creation of the same compressed file from an uncompressed original in addition to sound editing or mixing lossless audio compression is often used for archival storage or as master copies lossy audio compression edit comparison of spectrograms of audio in an uncompressed format and several lossy formats the lossy spectrograms show bandlimiting of higher frequencies a common technique associated with lossy audio compression lossy audio compression is used in a wide range of applications in addition to standalone audio only applications of file playback in mp3 players or computers digitally compressed audio streams are used in most video dvds digital television streaming media on the internet satellite and cable radio and increasingly in terrestrial radio broadcasts lossy compression typically achieves far greater compression than lossless compression by discarding less critical data based on psychoacoustic optimizations 50 psychoacoustics recognizes that not all data in an audio stream can be perceived by the human auditory system most lossy compression reduces redundancy by first identifying perceptually irrelevant sounds that is sounds that are very hard to hear typical examples include high frequencies or sounds that occur at the same time as louder sounds those irrelevant sounds are coded with decreased accuracy or not at all due to the nature of lossy algorithms audio quality suffers a digital generation loss when a file is decompressed and recompressed this makes lossy compression unsuitable for storing the intermediate results in professional audio engineering applications such as sound editing and multitrack recording however lossy formats such as mp3 are very popular with end users as the file size is reduced to 5 20 of the original size and a megabyte can store about a minute s worth of music at adequate quality several proprietary lossy compression algorithms have been developed that provide higher quality audio performance by using a combination of lossless and lossy algorithms with adaptive bit rates and lower compression ratios examples include aptx ldac lhdc mqa and scl6 coding methods edit to determine what information in an audio signal is perceptually irrelevant most lossy compression algorithms use transforms such as the modified discrete cosine transform mdct to convert time domain sampled waveforms into a transform domain typically the frequency domain once transformed component frequencies can be prioritized according to how audible they are audibility of spectral components is assessed using the absolute threshold of hearing and the principles of simultaneous masking the phenomenon wherein a signal is masked by another signal separated by frequency and in some cases temporal masking where a signal is masked by another signal separated by time equal loudness contours may also be used to weigh the perceptual importance of components models of the human ear brain combination incorporating such effects are often called psychoacoustic models 51 other types of lossy compressors such as the linear predictive coding lpc used with speech are source based coders lpc uses a model of the human vocal tract to analyze speech sounds and infer the parameters used by the model to produce them moment to moment these changing parameters are transmitted or stored and used to drive another model in the decoder which reproduces the sound lossy formats are often used for the distribution of streaming audio or interactive communication such as in cell phone networks in such applications the data must be decompressed as the data flows rather than after the entire data stream has been transmitted not all audio codecs can be used for streaming applications 50 latency is introduced by the methods used to encode and decode the data some codecs will analyze a longer segment called a frame of the data to optimize efficiency and then code it in a manner that requires a larger segment of data at one time to decode the inherent latency of the coding algorithm can be critical for example when there is a two way transmission of data such as with a telephone conversation significant delays may seriously degrade the perceived quality in contrast to the speed of compression which is proportional to the number of operations required by the algorithm here latency refers to the number of samples that must be analyzed before a block of audio is processed in the minimum case latency is zero samples e g if the coder decoder simply reduces the number of bits used to quantize the signal time domain algorithms such as lpc also often have low latencies hence their popularity in speech coding for telephony in algorithms such as mp3 however a large number of samples have to be analyzed to implement a psychoacoustic model in the frequency domain and latency is on the order of 23 ms speech encoding edit speech encoding is an important category of audio data compression the perceptual models used to estimate what aspects of speech a human ear can hear are generally somewhat different from those used for music the range of frequencies needed to con...
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