Multidimensional discrete convolution: Difference between revisions

Revision as of 16:35, 26 November 2024

Latest revision as of 06:50, 14 June 2025

Line 205:

# Zero pad the signals <math>h(n_1,n_2)</math> and <math>x(n_1,n_2)</math> such that they are both <math>N_1\times N_2</math> in size

# Compute the DFTs of both <math>h(n_1,n_2)</math> and <math>x(n_1,n_2)</math>

# MultipleMultiply the results of the DFTs to obtain <math>Y(k_1,k_2)=H(k_1,k_2)X(k_1,k_2)</math>

# The result of the IDFT of <math>Y(k_1,k_2)</math> will then be equal to the result of performing linear convolution on the two signals