Filtering in the Frequency Domain - DIP [closed]

1. What are the steps of filtering in frequency domain in dip?
2. What is filtering in frequency domain?
3. What is filtering in dip?
4. What are the advantages of filtering in frequency domain?

What are the steps of filtering in frequency domain in dip?

Frequency filters process an image in the frequency domain. The image is Fourier transformed, multiplied with the filter function and then re-transformed into the spatial domain. Attenuating high frequencies results in a smoother image in the spatial domain, attenuating low frequencies enhances the edges.

What is filtering in frequency domain?

Filtering in the frequency domain consists of modifying the Fourier transform of an image and then computing the inverse transform to obtain the processed result. A high-pass filter (which attenuates low frequencies) enhances sharp detail, but cause a reduction in contrast in the image.

What is filtering in dip?

Hence Filtering is a neighborhood operation, in which the value of any given pixel in the output image is determined by applying some algorithm to the values of the pixels in the neighborhood of the corresponding input pixel.

What are the advantages of filtering in frequency domain?

The reason for doing the filtering in the frequency domain is generally because it is computationally faster to perform two 2D Fourier transforms and a filter multiply than to perform a convolution in the image (spatial) domain. This is particularly so as the filter size increases.