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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.
Besides uncompressed formats and lossless compression formats that can usually be interconverted without any loss of detail, there are compressed formats such as JPEG, which lose detail on nearly every compress. While a conversion from a compressed to an uncompressed format is in general without loss, this is not true the other way around.
The format supports an optional alpha channel like PNG (but unlike JPEG); and progressive coding, similar to PNG (unlike it, progressive compression doesn't increase file-size), but as FLIF's algorithm is more complex (and partly, may not have had as much tuning of the implementation yet), it has a higher computational cost; at least lower ...
DCT is the basis for JPEG, a lossy compression format which was introduced by the Joint Photographic Experts Group (JPEG) in 1992. [34] JPEG greatly reduces the amount of data required to represent an image at the cost of a relatively small reduction in image quality and has become the most widely used image file format.
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. 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:
Most formats up until 2022 were for storing 2D images, not 3D ones. The data stored in an image file format may be compressed or uncompressed. If the data is compressed, it may be done so using lossy compression or lossless compression. For graphic design applications, vector formats are often used. Some image file formats support transparency.