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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.
The dictionary describes the properties of the image, and the stream contains the image data. (Less commonly, small raster images may be embedded directly in a page description as an inline image.) Images are typically filtered for compression purposes. Image filters supported in PDF include the following general-purpose filters:
Mixed raster content (MRC) is a method for compressing images that contain both binary-compressible text and continuous-tone components, using image segmentation methods to improve the level of compression and the quality of the rendered image. [1]
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]
Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (i.e. frequently encountered) data will produce shorter output than "improbable" data.
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