Now that we’ve covered the basic of convolution masks, I’d like to cover a few special ones that have interesting uses in image processing. We’ll assume for now that we are simply using 3×3 spatial convolution masks. A highly recommended experiment is to not only test these masks yourself, but to try making larger masks (ie: 5×5, 7×7, etc) of the same type to see what effects it may have. I have included a reference image with the examples below so that you may compare the before/after effects of these masks.

• Blurring/Averaging:
  • Mask:
  • Example:
  • Notes: If you increase the size of the mask, the denominator in each mask element should be the total number of “pixels” in the mask (ie: for a 5×5 mask, each element should be , as this prevents saturation of the output image)
• Motion Blurring (Diagonal):
  • Mask:
  • Example:
  • Notes: none
• Motion Blurring (Horizontal):
  • Mask:
  • Example:
  • Notes: A vertical blur can be achieved by simply “rotating” the mask matrix
• Edge Detection:
  • Mask:
  • Example:
  • Notes: The in the centre can be replaced with a zero; There are many ways to accomplish edge detection, and this is just one of them.