Noise refers to the unwanted or irrelevant information present in an image or video. It can be induced by diverse factors, such as sensor noise, compression artifacts, and environmental elements like lighting conditions and reflections. Noise has the potential to severely affect the quality and clarity of an image or video, making it more arduous to accurately analyze or interpret the image content.
Numerous methods can be employed to reduce or eliminate noise from images or videos, including image denoising algorithms and noise reduction techniques. Image denoising algorithms are engineered to eliminate noise from an image by pinpointing and filtering out the noise components. Meanwhile, noise reduction techniques involve applying filters or transformations to the image to lower the overall noise level.
Noise reduction is a vital step in numerous image processing and analysis tasks within the realm of computer vision. This is because it can enhance the precision and reliability of the results. It is particularly crucial in scenarios where the image or video contains critical information that requires accurate identification or assessment, such as in surveillance or medical image analysis applications.