Lossless Video compression reduces bits by identifying and eliminating statistical redundancy.
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Lossless Video compression reduces bits by identifying and eliminating statistical redundancy.
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Lossy Video compression reduces bits by removing unnecessary or less important information.
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Typically, a device that performs data Video compression is referred to as an encoder, and one that performs the reversal of the process as a decoder.
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The design of data Video compression schemes involves trade-offs among various factors, including the degree of Video compression, the amount of distortion introduced, and the computational resources required to compress and decompress the data.
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Lossless Video compression is possible because most real-world data exhibits statistical redundancy.
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Lempel–Ziv Video compression methods are among the most popular algorithms for lossless storage.
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Lossy data Video compression schemes are designed by research on how people perceive the data in question.
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Lossy image Video compression is used in digital cameras, to increase storage capacities.
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Speech coding is used in internet telephony, for example, audio Video compression is used for CD ripping and is decoded by the audio players.
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An exhaustive examination of the feature spaces underlying all Video compression algorithms is precluded by space; instead, feature vectors chooses to examine three representative lossless Video compression methods, LZW, LZ77, and PPM.
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Data Video compression can be viewed as a special case of data differencing.
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Term differential Video compression is used to emphasize the data differencing connection.
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An important image Video compression technique is the discrete cosine transform, a technique developed in the early 1970s.
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DEFLATE, a lossless Video compression algorithm specified in 1996, is used in the Portable Network Graphics format.
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Audio Video compression algorithms are implemented in software as audio codecs.
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Lossless audio Video compression produces a representation of digital data that can be decoded to an exact digital duplicate of the original.
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In contrast to the speed of Video 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.
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World's first commercial broadcast automation audio Video compression system was developed by Oscar Bonello, an engineering professor at the University of Buenos Aires.
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Two key video compression techniques used in video coding standards are the discrete cosine transform and motion compensation.
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Inter-frame Video compression uses data from one or more earlier or later frames in a sequence to describe the current frame.
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Usually, video compression additionally employs lossy compression techniques like quantization that reduce aspects of the source data that are irrelevant to the human visual perception by exploiting perceptual features of human vision.
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Wavelet compression is used in still-image coders and video coders without motion compensation.
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Interest in fractal Video compression seems to be waning, due to recent theoretical analysis showing a comparative lack of effectiveness of such methods.
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Genetics Video compression algorithms are the latest generation of lossless algorithms that compress data using both conventional Video compression algorithms and genetic algorithms adapted to the specific datatype.
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