How does digital filtering improve the quality of a signal?

Digital filtering enhances the quality of a signal primarily by removing unwanted noise or artifacts. In various applications, signals can be contaminated by noise that masks the true information contained within the desired signal. Digital filters process the signal through algorithms that can identify and suppress these unwanted components based on their frequency characteristics.

For instance, a low-pass filter can effectively diminish high-frequency noise while preserving the lower-frequency components which could represent the actual signal of interest. This targeted approach leads to a clearer and more interpretable signal, making it easier for subsequent analysis or interpretation.

While other options may have utility in certain contexts, they do not address the fundamental role of digital filtering in the context of signal quality. Amplifying the signal, changing its format, or increasing the sample rate do not inherently improve the clarity or integrity of the original information contained in the signal. These actions can sometimes be necessary for signal processing but do not directly equate to the benefits provided by the removal of unwanted noise, which is the core function of digital filtering.