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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.
Images can be added to this category by placing the {{Overcompressed JPEG}} template on the image description page. Media in category "Images with excessive JPEG compression" The following 57 files are in this category, out of 57 total.
Continuously varied JPEG compression (between Q=100 and Q=1) for an abdominal CT scan. JPEG (/ ˈ dʒ eɪ p ɛ ɡ / JAY-peg, short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) [2] [3] is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography.
Video can be compressed immensely (e.g., 100:1) with little visible quality loss; Audio can often be compressed at 10:1 with almost imperceptible loss of quality; Still images are often lossily compressed at 10:1, as with audio, but the quality loss is more noticeable, especially on closer inspection.
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 ...
The format was designed to facilitate the quick downloading of images, among other things. [1] Originally, the compression was developed by the Johnson-Grace Company, [2] which was then acquired by AOL. [3] When an image is converted to the ART format, the image is analyzed and the software decides what compression technique would be best. [2]
Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum (discrete) value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible.
JBIG2 is an image compression standard for bi-level images, developed by the Joint Bi-level Image Experts Group.It is suitable for both lossless and lossy compression. . According to a press release [1] from the Group, in its lossless mode JBIG2 typically generates files 3–5 times smaller than Fax Group 4 and 2–4 times smaller than JBIG, the previous bi-level compression standard released by