Another very popular image processing task in which blurring is used, is removing noise from images. Images can be distorted because of various reasons such as, for example, from their scanning process, where the film grain adds unwanted noise, but the scanner could also introduce noise, or the photograph to be scanned might have aesthetic marks on it (such as scratches). Furthermore, even digital photographs may have noise in them, for example, due to their CCD detectors. Transmitting images over electronic mediums may also corrupt them, leading to a noisy result. Many types of additive noise have been implemented in the Image Processing Toolbox of MATLAB and they can be used to simulate some of the aforementioned image corruptions. The function that is used for adding noise to an image is called imnoise. Its usage can be explored using help. Let's see the first lines of the result:
>> help imnoise
The output of the preceding command is as follows:
imnoise...