Extended Gaussian Images


We can extend this process so that

An example of such an extended Gaussian image is shown in Fig. 44.  

Fig. 44 The EGI of a block
Using three-dimensional solid models of objects (see next section),
Disadvantages:
 
Fig. 45 Examples of objects with the same EGI

Gaussian function demos


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.

Smoothing nonnoisy image

lena.gif filtered with sigma = 3 filtered with sigma = 1

Noise cancelling

noisy lena filtered with sigma = 3 filtered with sigma =1

(Noise is generated by matlab function 0.3*randn(512))