Lossless data compression algorithms usually exploit statistical redundancy to represent data without losing any information, so that the process is reversible. Lossless compression is possible because most real-world data exhibits statistical redundancy. For example, an image may have areas of colour that do not change over several pixels; instead of coding "red pixel, red pixel, ..." the data may be encoded as "279 red pixels". This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy.
Lossless data compression algorithms usually exploit statistical redundancy to represent data without losing any information , so that the process is reversible . Lossless compression is possible because most real - world data exhibits statistical redundancy . For example , an image may have areas of colour that do not change over several pixels ; instead of coding " red pixel , red pixel , ... " the data may be encoded as " 279 red pixels " . This is a basic example of run - length encoding ; there are many schemes to reduce file size by eliminating redundancy .
What usually exploits statistical redundancy?
What usually exploits statistical redundancy ?
Lossless data compression algorithms
Lossless data compression algorithms