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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.
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:
For example, an HD 1080 picture has 1080 lines (rows) of pixels. An odd field consists of pixel information for lines 1, 3, 5...1079. An even field has pixel information for lines 2, 4, 6...1080. When video is sent in interlaced-scan format, each frame is sent in two fields, the field of odd-numbered lines followed by the field of even-numbered ...
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.
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).
Uncompressed video is digital video that either has never been compressed or was generated by decompressing previously compressed digital video. It is commonly used by video cameras, video monitors, video recording devices (including general-purpose computers), and in video processors that perform functions such as image resizing, image rotation, deinterlacing, and text and graphics overlay.
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