Data compression
Also known as: source coding · bit-rate reduction · compression
- 1Reduces the number of bits required to represent information.
- 2Lossless compression allows for the exact reconstruction of original data.
- 3Lossy compression discards less important information to achieve higher efficiency.
- 4An encoder performs the compression, while a decoder performs the decompression.
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation.
Connections2
Practical application of entropy limits
Shannon's source coding theorem establishes that the entropy of a source sets a fundamental limit on the maximum lossless data compression achievable.
Practical application of information theory
Information theory provides the mathematical bounds for data compression, explaining how much redundancy can be removed from a signal without losing information.
Data compression, also known as source coding or bit-rate reduction, is the process of encoding information to occupy fewer bits than its original representation. This technique is essential for efficient data storage and transmission in digital systems.
Composite image showing JPG and PNG image compression. Left side of the image is from a JPEG image, showing lossy artifacts; the right side is from a PNG image.Wikimedia Commons: File:Comparison_of_JPEG_and_PNG.pngComparison of two revisions of a fileWikimedia Commons: File:Nubio_Diff_Screenshot3.pngComparison 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.Wikimedia Commons: File:AudiodatenkompressionManowarThePowerOfThySword.jpgSolidyne 922: The world's first commercial audio bit compression sound card for PC, 1990Wikimedia CommonsProcessing stages of a typical video encoderWikimedia Commons Compression is categorized into two primary types: lossless and lossy. Lossless compression eliminates statistical redundancy without any loss of information, allowing for perfect reconstruction. Conversely, lossy compression removes less important data to achieve greater reduction. The process is managed by an encoder, while the reversal of the process is performed by a decoder.