Video compression

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Video compression deals with the compression of digital video data. Video compression is necessary for efficient coding of video data in video file formats and streaming video formats. Compression is a conversion of data to a format that requires fewer bits, usually performed so that the data can be stored or transmitted more efficiently. If the inverse of the process, decompression, produces an exact replica of the original data then the compression is lossless. Lossy compression, usually applied to image data, does not allow reproduction of an exact replica of the original image, but it is more efficient. While lossless video compression is possible, in practice it is virtually never used, and all standard video data rate reduction involves discarding data.

Video is basically a three-dimensional array of color pixels. Two dimensions serve as spatial (horizontal and vertical) directions of the moving pictures, and one dimension represents the time domain.

A frame is a set of all pixels that (approximately) correspond to a single point in time. Basically, a frame is the same as a still picture. However, in interlaced video, the set of horizontal lines with even numbers and the set with odd numbers are grouped together in fields. The term "picture" can refer to a frame or a field.

However, video data contains spatial and temporal redundancy. Similarities can thus be encoded by merely registering differences within a frame (spatial) and/or between frames (temporal). Spatial encoding is performed by taking advantage of the fact that the human eye is unable to distinguish small differences in colour as easily as it can changes in brightness and so very similar areas of colour can be "averaged out" in a similar way to jpeg images (JPEG image compression FAQ, part 1/2). With temporal compression only the changes from one frame to the next are encoded as often a large number of the pixels will be the same on a series of frames (About video compression).

Video compression typically reduces this redundancy using lossy compression. Usually this is achieved by image compression techniques to reduce spatial redundancy from frames (this is known as intraframe compression or spatial compression) and motion compensation and other techniques to reduce temporal redundancy (known as interframe compression or temporal compression). Formats such as DV avoid interframe compression to allow easier non-linear editing.

Today, nearly all video compression methods in common use (e.g., those in standards approved by the ITU-T or ISO) apply a discrete cosine transform (DCT) for spatial redundancy reduction. Other methods, such as fractal compression, matching pursuits, and the use of a discrete wavelet transform (DWT) have been the subject of some research, but are typically not used in practical products (except for the use of wavelet coding as still-image coders without motion compensation). Interest in fractal compression seems to be waning, due to recent theoretical analysis showing a comparative lack of effectiveness to such methods.

The use of most video compression techniques (e.g., DCT or DWT based techniques) involves quantization. The quantization can either be scalar quantization or vector quantization; however, nearly all practical designs use scalar quantization because of its greater simplicity.

In broadcast engineering, digital television (DVB, ATSC and ISDB ) is made practical by video compression. TV stations can broadcast not only HDTV, but multiple virtual channels on the same physical channel as well. It also conserves precious bandwidth on the radio spectrum. Nearly all digital video broadcast today uses the MPEG-2 standard video compression format, although H.264/MPEG-4 AVC and VC-1 are emerging contenders in that domain.