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Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data. [1]
For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes: C o m p r e s s i o n R a t i o = U n c o m p r e s s e d D a t a R a t e C o m p r e s s e d D a t a R a t e {\displaystyle {\rm {Compression\;Ratio}}={\frac {\rm ...
WhatsApp (officially WhatsApp Messenger) is an American instant messaging (IM) and voice-over-IP (VoIP) service owned by technology conglomerate Meta. [13] It allows users to send text, voice messages and video messages, [14] make voice and video calls, and share images, documents, user locations, and other content.
A compression artifact (or artefact) is a noticeable distortion of media (including images, audio, and video) caused by the application of lossy compression. Lossy data compression involves discarding some of the media's data so that it becomes small enough to be stored within the desired disk space or transmitted ( streamed ) within the ...
Composite image showing JPG and PNG image compression. Left side of the image is from a low-quality JPEG image, showing lossy artefacts; the right side is from a PNG image. In information technology , lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data ...
Composite image showing JPG and PNG image compression. Left side of the image is from a JPEG image, showing lossy artefacts; the right side is from a PNG image. In the late 1980s, digital images became more common, and standards for lossless image compression emerged. In the early 1990s, lossy compression methods began to be widely used. [14]
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By operation of the pigeonhole principle, no lossless compression algorithm can shrink the size of all possible data: Some data will get longer by at least one symbol or bit. Compression algorithms are usually effective for human- and machine-readable documents and cannot shrink the size of random data that contain no redundancy. Different ...