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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.
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:
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.
A variety of technologies soon emerged to do so. The primary goal for most methods of compressing video is to produce video that most closely approximates the fidelity of the original source, while simultaneously delivering the smallest file-size possible. However, there are also several other factors that can be used as a basis for comparison.
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).
MPEG-1 is a standard for lossy compression of video and audio.It is designed to compress VHS-quality raw digital video and CD audio down to about 1.5 Mbit/s (26:1 and 6:1 compression ratios respectively) [2] without excessive quality loss, making video CDs, digital cable/satellite TV and digital audio broadcasting (DAB) practical.
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