Hands-On Image Processing with Python

Application of the convolution theorem

The convolution theorem says that convolution in an image domain is equivalent to a simple multiplication in the frequency domain:

Following diagram shows the application of fourier transforms:

The next diagram shows the basic steps in frequency domain filtering. We have the original image, F, and a kernel (a mask or a degradation/enhancement function) as input. First, both input items need to be converted into the frequency domain with DFT, and then the convolution needs to be applied, which by convolution ...