Video Production Quantisation

Quantisation

Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. For example, reducing the number of colors required to represent a digital image makes it possible to reduce its file size. Specific applications include DCT data quantization in JPEG and DWT data quantization in JPEG 2000.

Colour quantization reduces the number of colours used in an image; this is important for displaying images on devices that support a limited number of colours and for efficiently compressing certain kinds of images. Most bitmap editors and many operating systems have built-in support for colour quantization. Popular modern colour quantization algorithms include the nearest colour algorithm (for fixed palettes), the median cut algorithm, and an algorithm based on octrees.

It is common to combine colour quantization with dithering to create an impression of a larger number of colours and eliminate banding artefacts.

The human eye is fairly good at seeing small differences in brightness over a relatively large area, but not so good at distinguishing the exact strength of a high frequency brightness variation. This fact allows one to get away with a greatly reduced amount of information in the high frequency components. This is done by simply dividing each component in the frequency domain by a constant for that component, and then rounding to the nearest integer. This is the main lossy operation in the whole process. As a result of this, it is typically the case that many of the higher frequency components are rounded to zero, and many of the rest become small positive or negative numbers.