Digital Video

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Sampling & Scaling

Everythings Going Digital

The color-space conversion allows for different digitization sampling rates for luminance and chrominance. Typically studio quality video (MPEG-2 scheme, other formats sample at different rates), requires that the chrominance U & V values only be sampled twice for every 4 times the Y luminance value is sampled. This discards half of the less important color information. Two popular digital video formats, the MPEG and the DVI take only one UV sample for every 2 X 2 square of luminance Y pixels. This achieves a 2 to 1 compression.

Good Things Come in Small Packages

The easiest way to save memory is to store less. The preprocessing technique of scaling adheres to this maxium. Original digital video standards only stored a video window of 160 X 120 pixels. A reduction of 1/16th the size of a 640 X 480 window. With faster processors a 320 X 240 video window size is quickly becoming the standard, yielding a 4 to 1 compression. A further scaling application involves time instead of space. In this temporal scaling the number of frames per second (fps), is reduced from 30 to 24. If the fps is reduced below 24 the reduction becomes very noticable in the form of jerky movement.

There is Only One Constant in the World, Change

The first actual compression step is transformation. Codecs (COmpressionDECompression algorithms), transform the two-dimensional spatial representation of an image into another dimension space (frequency). Since most natural images are composed of low frequency information, the high frequency components can be discarded. This results in a softer picture in terms of contrast. The frequency information is represented as 64 coefficients due to the underlying DCT (Discrete Cosine Transform), algorithm which operates upon 8 X 8 pixel grids. Low frequency terms occur in one corner of the grid, with high frequency terms occurring in the opposite corner of the grid.

If You Don't Need It, Lose It

The lossy quantization step of digital video uses fewer bits to represent larger quantities. The 64 frequency coefficients of the DCT transformation are treated as real numbers. These are quantified into 16 different levels. The high frequency components (sparse in real-world images), are represented with only 0, 1 or 2 bits. The zero mapped frequencies drop out and are lost.