Hi Premnath,
I understand that you want to uderstand the Part 2 of the code for an Ideal Low-Pass Filter, focusing on how it manipulates frequency indices and sets up the frequency domain.
Here is the explantion of the important steps of the code you have provided:
Frequency Indexing:
This part of the code generates frequency index vectors u and v for the image dimensions. It then adjusts indices greater than half the size to negative values, effectively centering the zero frequency.
u = 0:(M-1); v = 0:(N-1);
u(u > M/2) = u(u > M/2) - M;
v(v > N/2) = v(v > N/2) - N;
Meshgrid Creation:
Here, the code uses “meshgrid” to create a 2D grid of frequency coordinates. This grid is used to map out the frequency space, allowing for further calculations.
[V, U] = meshgrid(v, u);
Distance Calculation:
This section calculates the Euclidean distance D from the origin for each point in the frequency domain. This distance helps in defining the boundary of the filter.
D = sqrt(U.^2 + V.^2);
Example Explanation:
For an 8x8 matrix, this code shifts the frequency indices so that they range symmetrically around zero, like turning u into [0 1 2 3 4 -3 -2 -1], which is crucial for centering.
Purpose in Filtering:
By setting up D, the code allows you to apply a circular filter, retaining frequencies within a specified cutoff P and attenuating others, effectively filtering the image.
Refer to the documentation of “meshgrid” function to know more about its usage:
Hope this helps!
