These demos show the basic effects of the (2D) Gaussian filter: smoothing the image and wiping off the noise. Generally speaking, for a noise-affected image, smoothing it by Gaussian function is the first thing to do before any other further processing, such as edge detection. The effectiveness of the gaussian function is different for different choices of the standard deviation sigma of the Gaussian filter. You can see this from the following demos.
lena.gif | filtered with sigma = 3 | filtered with sigma = 1 |
---|---|---|
noisy lena | filtered with sigma = 3 | filtered with sigma =1 |
---|---|---|