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Kernel (image processing)

Matrix used in image processing to alter an image

  • 12 min read
  • 2 chapters

Related on Lably

Through Digital image processing, Matrix (mathematics) and Convolution

Details

The general expression of a convolution is

gx,y=ω∗fx,y=∑i=−aa∑j=−bbωi,jfx−i,y−j,

where g(x,y) is the filtered image, f(x,y) is the original image, ω is the filter kernel. Every element of the filter kernel is considered by −a≤i≤a and −b≤j≤b.

Depending on the element values, a kernel can cause a wide range of effects:

The above are just a few examples of effects achievable by convolving kernels and images.

Origin

The origin is the position of the kernel which is above (conceptually) the current output pixel. This could be outside of the actual kernel, though usually it corresponds to one of the kernel elements. For a symmetric kernel, the origin is usually the center element.

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