Which information do we get from phase spectrum about an Image?

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I know about Phase of 1 D signal , but when I move into higher dimensions like 2D or 3D etc, it becomes headache to grasp the concept.
I have computed phase spectrum of 2 images but I don't know how to study them. Which information do we get from phase spectrum of an Image? Can anybody explain from the below results?
clc;
clear all;
close all;
image1=imread('D:\baby1.jpg');
image1=rgb2gray(image1);
image2=imread('D:\baby2.jpg');
image2=rgb2gray(image2);
f1=fft2(image1);
f1=log(1+fftshift(f1));
f2=fft2(image2);
f2=log(1+fftshift(f2));
phase1=angle(f1);
phase2=angle(f2);
figure,
subplot(2,2,1);
imshow(image1);
title('Baby Gray scale Image 1');
subplot(2,2,3);
imshow(image2);
title('Baby Gray scale Image 2');
subplot(2,2,2);
imshow(phase1,[]);
title('Phase Spectrum of Baby Image1');
subplot(2,2,4);
imshow(phase2,[]);
title('Phase Spectrum of Baby Image2');

Answers (1)

Christiaan
Christiaan on 20 May 2015
Edited: Christiaan on 20 May 2015
Dear Ramdas,
Computing the 2-D Fourier transform is mathematically equivalent to computing the 1-D Fourier transform of all the rows and then computing the 1-D Fourier transforms of all the columns of the result. The order (row-first or column-first) doesn't actually matter.
Two good examples can be found here:
You can first try to understand how the first example works (detailedly). And the use the difficult example to apply. If you program that in MATLAB it should help you. When you also get that example, you probably can explain yourself the result you obtained.
Hint: The fourier transform of a dirac pulse is a line in the fourier space. The fourier transform of a line is an impuls in the fourier space.
Good luck! Christiaan

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