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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.
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:
Compression of an image to reduce file size (in Kb) is usually "lossy" and is not advised for featured pictures. Image compression will reduce download times and save disk space, but it does so at the expense of fine detail and overall image quality. If in doubt, when saving JPEG files, always select the "maximum" quality setting.
If the picture contains an area of the same color, it can be compressed without loss by saying "200 red dots" instead of "red dot, red dot, ...(197 more times)..., red dot." The original data contains a certain amount of information, and there is a lower bound to the size of a file that can still carry all the information.
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.
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Three types of pictures (or frames) are used in video compression: I, P, and B frames. An I‑frame (intra-coded picture) is a complete image, like a JPG or BMP image file. A P‑frame (Predicted picture) holds only the changes in the image from a previous frame. For example, in a scene where a car moves across a stationary background, only the ...