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In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content.
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
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.
Lossless compression should be used to avoid accumulating stages of re-compression when editing images. Lossy compression algorithms preserve a representation of the original uncompressed image that may appear to be a perfect copy, but is not a perfect copy. Often lossy compression is able to achieve smaller file sizes than lossless compression.
Jon Sneyers, one of the developers of FLIF, since combined it with ideas from various lossy compression formats to create a successor called the Free Universal Image Format (FUIF), which itself was combined with Google's PIK format to create JPEG XL. As a consequence, FLIF is no longer being developed. [1]
Compression algorithm Raster/ vector Maximum Color depth. Indexed color Trans-parency. Meta-data. Inter-lacing. Multi-page Anima-tion Layers Color manage-ment Extend- able HDR format CMYK; AI: Lossy and lossless Both 8 bpc Yes Yes Yes No Yes No Yes Yes — No AVIF: AV1 Lossy and lossless: Raster 12 bpc No Yes Yes No No Yes No Yes Yes Yes No ...
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.
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 ...