Difference between revisions of "Lossy data compression"

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(Created page with "The term <nowiki>"Lossy data compression"</nowiki> is used to describe a process where processing is applied to data to reduce the total amount of data. In <nowiki>lossy data com...")
 
 
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The term <nowiki>"Lossy data compression"</nowiki> is used to describe a process where processing is applied to data to reduce the total amount of data. In <nowiki>lossy data compression</nowiki> some of the original information is discarded. The result is that an ''approximation'' of the original information is encoded in the output data and the total amount of data is reduced (thus the term "compression").
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The term <nowiki>"Lossy data compression"</nowiki> is used to describe a method where processing is applied to data to reduce the total amount of data. In <nowiki>lossy data compression</nowiki> some of the original information is discarded. The result is that an ''approximation'' of the original information is encoded in the output data and the total amount of data is reduced (thus the term "compression").
  
What makes <nowiki>lossy data compression</nowiki> useful is the human mind's ability to "fill in the missing details" and most lossy data compression schemes involve some form of [[perceptual coding]] based on research on human perception.
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What makes <nowiki>lossy data compression</nowiki> useful is the human mind's ability to "fill in the missing details." Most <nowiki>lossy data compression</nowiki> schemes involve some form of [[perceptual coding]] based on research on human perception.
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See [[data compression]] for details.
  
 
[[Category:Terminology]]
 
[[Category:Terminology]]

Latest revision as of 17:38, 24 February 2012

The term "Lossy data compression" is used to describe a method where processing is applied to data to reduce the total amount of data. In lossy data compression some of the original information is discarded. The result is that an approximation of the original information is encoded in the output data and the total amount of data is reduced (thus the term "compression").

What makes lossy data compression useful is the human mind's ability to "fill in the missing details." Most lossy data compression schemes involve some form of perceptual coding based on research on human perception.

See data compression for details.