Harmonics in 2-D FFT Signal In case of 1-D FFT it is far more easier to find number of harmonics and their Respective frequencies and amplitudes.
Lets say if i have 8 points signal the harmonics of it then would be 7 with one DC point i.e,



the harmonics after 4th points would have negative imaginary part as it below the nyquist rate.

but if I've 2D signal of 8x8 Matrix there would be total of 64 harmonics and the Nyquist rate will then be on the 32nd point. Am i right ?

If my above statement is correct, the fractional frequency for the first harmonic then would be ,

0 -> Dc
1st Harmonic - > 1/64 -> 64 samples in 1 cycle

Number of Cycle 1.
Number of samples = 64
Sampling rate = 0.015625

What would then be the actual frequency of this Harmonic , I am asking this because i couldn't be able to identify it when i am plotting it on Matlab.
Your diagram is incorrect. Computing the 2D-FFT of a 8x8 matrix is not the same as computing the 1D-FFT of a 1x64 vector. A 2D-FFT is "probing" your signal with templates which have both an horizontal and vertical frequency. A signal with a low horizontal frequency and a null vertical frequency is a progressive horizontal gradient. A signal whose vertical and horizontal frequency are both the nyquist frequency is a checkerboard pattern...

If you take an image and perform a 2D-FFT on it, you will find in the resulting matrix the following elements:


Cell (1, 1): DC component (average of all values in the matrix).
Cell (2, 1): first horizontal harmonic; frequency 1/8.
Cell (3, 1): second horizontal harmonic; frequency 2/8.
Cell (4, 1): third horizontal harmonic; frequency 3/8.
Cell (5, 1): fourth horizontal harmonic; frequency 4/8 (Nyquist).
Cell (6, 1): third horizontal negative freq. harmonic; frequency -3/8.
Cell (7, 1): second horizontal negative freq. harmonic; frequency -2/8.
Cell (8, 1): first horizontal negative freq. harmonic; frequency -1/8.
Cell (1, 2): first vertical harmonic; frequency 1/8.
Cell (1, 3): second vertical harmonic; frequency 2/8.
...
Cell (5, 5): fourth horizontal/vertical harmonic (Checkerboard pattern).
...


A good way to visualize this is to compute the 2D IFFT of a single pixel at each of the 64 positions of the matrix, and look at the real part.