Functions > Image Processing > Convolution and Filters > Smoothing
  
Smoothing
centsmooth(M)—Returns matrix M smoothed with a 3 × 3 center weighted kernel.
The function returns a matrix containing the smoothed image. At the edges of the image, the kernel does not completely overlap the image; therefore, these edge pixels are only convolved with a subset of the kernel and divided by the appropriate normalizing factor.
When convolving the specified 3 x 3 smoothing kernel with the image matrix M, the function uses averaging to replace the value at a pixel by a weighted average involving its value and that of its neighbors. The weights are stored in a square matrix which is convolved with the image to produce the smoothed image.
Arguments
M is an image matrix.
Additional Information
Smoothing is an important technique for noise reduction and differentiating artifacts in an image. Smoothing eliminates minor random noise, but is most effective on uniform, smoothly varying types of noise, like Gaussian noise.
The centsmooth function convolves matrix M with the following kernel matrix which gives more weight to the center pixel.