Median Filtering
The median filter is normally used to reduce noise in an image, somewhat like the mean filter. However, it often does a better job than the mean filter of preserving useful detail in the...
Category: Neighborhood Processing
Neighborhood Processing
Gaussian Blur Filter
The Gaussian blur filter is the best-known example of a LPF implemented with a nonuniform kernel. The mask coefficients for the Gaussian blur filter are samples from a 2D Gaussian function : The parameter...
Mean Filtering
The mean (also known as neighborhood averaging) filter is perhaps the simplest and most widely known spatial smoothing filter. It uses convolution with a (usually 3 ×3) mask whose coefficients have a value of...
Standard examples of Convolution Masks
Image filtering allows you to apply various effects on photos. The type of image filtering described here uses a 2D filter similar to the one included in Paint Shop Pro as User Defined Filter...
Convolution in the Two Dimensional Domain
The mathematical definition for 2D convolution is : In practice, this is rewritten as : where m2 is equal to half of the mask’s width and n2 is equal to half of the mask’s...
Convolution in the One Dimensional Domain
Convolution is a widely used mathematical operator that processes an image by computing—for each pixel—a weighted sum of the values of that pixel and its neighbors. Depending on the choice of weights, a wide...
Neighborhood Processing
Neighborhood-oriented operations perform techniques are those image processing techniques in which the resulting value for a pixel at coordinates (x0, y0)—which we shall call the reference pixel—is a function of the original pixel value...