Editing Quantization (signal processing) (section)

{{Short description|Process of mapping a continuous set to a countable set}}
{{Use American English|date=April 2019}}

[[File:Quantization error.png|thumb|upright=2|The simplest way to quantize a signal is to choose the digital amplitude value closest to the original analog amplitude. This example shows the original analog signal (green), the quantized signal (black dots), the [[Signal reconstruction|signal reconstructed]] from the quantized signal (yellow) and the difference between the original signal and the reconstructed signal (red). The difference between the original signal and the reconstructed signal is the quantization error and, in this simple quantization scheme, is a deterministic function of the input signal.]]

'''Quantization''', in mathematics and [[digital signal processing]], is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite [[number of elements]].  [[Rounding]] and [[truncation]] are typical examples of quantization processes.  Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding.  Quantization also forms the core of essentially all [[lossy compression]] algorithms.

The difference between an input value and its quantized value (such as [[round-off error]]) is referred to as '''quantization error''', '''noise''' or '''distortion'''.  A device or [[algorithm function|algorithmic function]] that performs quantization is called a '''quantizer'''.  An [[analog-to-digital converter]] is an example of a quantizer.