Kvantisaatiovirheitä

Kvantisaatiovirheitä, known in English as quantization errors, occur when a continuous range of values is mapped to a smaller, finite set of discrete values. This process is fundamental to digital signal processing and data conversion. For example, when an analog signal is converted to a digital signal by an analog-to-digital converter (ADC), the voltage or amplitude is measured at discrete time intervals. Each measurement is then assigned the closest available discrete digital value. The difference between the actual analog value and the assigned digital value is the quantization error.

These errors are inherent in the quantization process and are unavoidable when representing analog information in a digital format. The magnitude of the quantization error is typically limited to half the value of the least significant bit (LSB) of the digital representation. Reducing quantization error can be achieved by increasing the number of bits used in the digital representation, which effectively increases the number of discrete levels available and thus reduces the step size between them.

Quantization errors can manifest as noise in audio signals, distortion in image data, or inaccuracies in measurements. In digital audio, for instance, lower bit depths lead to more noticeable quantization noise, particularly at lower signal amplitudes. In image processing, quantization errors can cause banding artifacts in smooth gradients. Understanding and managing quantization errors is crucial for maintaining signal fidelity and achieving desired performance in various digital systems.