image kernels are 2D convolutions, and you can think of them as extensions from 1D convolutions. In 1D, understanding the frequency domain behavior is much easier since you don't have to worry about spacial frequency and 1D frequency is something most people can intuitively understand.

look at FIR filters, they are essentially 1D image kernels.