There is a well-understood math behind it. For blur, you can either do two things: - generate a matrix such that each element in the matrix is equal to 1 (e.g

There is a well-understood math behind it. For blur, you can either do two things: - generate a matrix such that each element in the matrix is equal to 1 (e.g. averaging) - generate a matrix such that it represents the Gaussian distribution (you can use a 2D Gauss function) For edge detection, you essentially have "derivative", e.g. rate of change; the more abrupt the change, the brighter the resulting pixel, hence why edges are highlighted. A good convolution kernel for edge detection would be the Laplacian. For sharpness, it's pretty much the Laplacian Kernel + identity kernel.