quantizationnoisena

Quantization noise is a form of signal distortion that occurs when a continuous analog signal is converted into a discrete digital signal. This process, known as quantization, involves representing a range of analog values with a limited number of discrete digital levels. Since the original analog signal can take on infinitely many values within a given range, approximating these values with a finite set of digital levels inevitably introduces an error. This error is the quantization noise.

The magnitude of quantization noise is directly related to the number of bits used to represent the digital signal. A higher number of bits allows for more discrete levels, thus a finer approximation of the original analog signal and a lower level of quantization noise. Conversely, fewer bits lead to coarser approximations and more significant quantization noise. This noise is often modeled as a random error uniformly distributed within a certain range, typically between half the value of the least significant bit and plus half the value of the least significant bit.

Quantization noise can impact the quality of digital audio, images, and other sampled data. In audio, it can manifest as a subtle hiss or a loss of dynamic range. In images, it can cause banding artifacts or a reduction in the perceived detail. Techniques such as dithering, which involves adding a small amount of random noise to the signal before quantization, can be employed to spread the quantization error across a wider range of frequencies, making it less noticeable and improving the perceived quality of the digitized signal.