Noise filtering is the process of reducing unwanted or irrelevant signals from data while preserving the information that is useful for analysis. Noise can appear as random fluctuations, distortions, interference, or other unwanted variations in sources such as images, audio, video, sensor readings, and network data.
For example, a surveillance camera operating in low-light conditions may capture an image with grainy visual noise. A filtering method can suppress these unwanted variations while retaining important features such as edges, shapes, and objects. Depending on the type of data, filtering techniques may include smoothing, frequency-based filtering, statistical methods, or machine-learning-based approaches. Noise filtering is widely used in computer vision, speech processing, IoT systems, medical imaging, telecommunications, and industrial monitoring.
