Howtosignalprocessing
- How do I know what size Gaussian filter to buy?
- What are the roles of the Gaussian filter parameters and the kernel size for filtering an image?
- When Gaussian filter is applied to an image it performs?
- How does the standard deviation parameter of the Gaussian filter affect the spatial filtering operation?
How do I know what size Gaussian filter to buy?
For example if sigma = 1 then the gaussian is greater than epsilon = 0.01 when x <= 2.715 so a filter radius = 3 (width = 2*3 + 1 = 7) is sufficient. If you reduce/increase epsilon then you will need a larger/smaller radius.
What are the roles of the Gaussian filter parameters and the kernel size for filtering an image?
The Gaussian filter is a non-uniform low pass filter. The kernel coefficients diminish with increasing distance from the kernel's centre. Central pixels have a higher weighting than those on the periphery. Larger values of σ produce a wider peak (greater blurring).
When Gaussian filter is applied to an image it performs?
A Gaussian Filter is a low pass filter used for reducing noise (high frequency components) and blurring regions of an image. The filter is implemented as an Odd sized Symmetric Kernel (DIP version of a Matrix) which is passed through each pixel of the Region of Interest to get the desired effect.
How does the standard deviation parameter of the Gaussian filter affect the spatial filtering operation?
Smoothing filters are typically used for noise reduction and for blurring. The standard deviation of the Gaussian function controls the amount of blurring. A large standard deviation (i.e., > 2) significantly blurs, while a small standard deviation (i.e., 0.5) blurs less.
