# Convolve NxM

The Convolve NxM operator modifies an input image with a NxM kernel to generate a new output image which can then be used for further image processing or analysis. Depending on the values you choose for the kernel, the operator can sharpen edge information, detect edges, or perform a smoothing function over the original image. See the topic Convolve 3x3 Operator for an example of heightening edge information with a 3x3 kernel.

Images that show a lower spatial frequency might require a larger kernel to effectively process the image. For example, you might use an NxM kernel to smooth out changes that occur over a larger number of pixels than the 3x3 Convolve operator can handle.

The size of the NxM kernel must be represented by an odd integer for both the width and height. In addition, the origin of the kernel is always at the center, unlike the 3x3 Convolve operator where you can specify which pixel is the origin.