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Usually, video compression additionally employs lossy compression techniques like quantization that reduce aspects of the source data that are (more or less) irrelevant to the human visual perception by exploiting perceptual features of human vision. For example, small differences in color are more difficult to perceive than are changes in ...
Video is almost always stored using lossy compression to reduce the file size. A video file normally consists of a container (e.g. in the Matroska format) containing visual (video without audio) data in a video coding format (e.g. VP9) alongside audio data in an audio coding format (e.g. Opus).
The compression ratio (that is, the size of the compressed file compared to that of the uncompressed file) of lossy video codecs is nearly always far superior to that of the audio and still-image equivalents. Video can be compressed immensely (e.g., 100:1) with little visible quality loss
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:
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These different algorithms for video frames are called picture types or frame types. The three major picture types used in the different video algorithms are I, P and B. [1] They are different in the following characteristics: I‑frames are the least compressible but don't require other video frames to decode.