peak value at the centre of F(0,0) in magnitude plot of fourier transform
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According to this doc
consists of a single line when Im using this
FT=fft2(linkImage);
freqz(linkImage)
In the doc it is mentioned that the center at F(0,0)of fourier tarnsform contains sum of all values in FT.But in my image along with the centre peak two more peaks are visible.Can someone explain what are they.
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Wayne King
2011년 11월 16일
Hi, I don't see how you are calling freqz() on an image.
freqz() expects two input vectors, or is this not a MATHWORKS' freqz?
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Wayne King
2011년 11월 22일
Didn't I show this already?
rng default;
x = randn(20,20);
xdft2 = fft2(x);
sum(x(:))
xdft2(1,1)
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Wayne King
2011년 11월 16일
At any rate, I think only when you shift the 2-D Fourier transform does it end up in the middle. Note that:
rng default;
x = randn(20,20);
xdft2 = fft2(x);
sum(x(:))
xdft2(1,1)
Now
xdft2 = fftshift(xdft2);
xdft2(11,11)
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Wayne King
2011년 11월 17일
You wrote freqz() above. freqz2() is for a filter.
For example:
h = 0.01*ones(10,10);
sum(h(:))
H = freqz2(h,10,10);
H(6,6)
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Wayne King
2011년 11월 17일
freqz2() is for a 2-D FIR filter, freqz() handles both FIR and IIR filters. You can infer the frequency response for your 2-D FIR filter from the 1-D response with freqz() iff your 2-D FIR filter is separable, but I wouldn't assume that this always the case.
Image Analyst
2011년 11월 22일
Come on, obviously "F(0,0)of Fourier transform contains sum of all values in FT" is NOT CORRECT. It simply can't be (unless your FT is a delta function) - just think about it for half a second. The F(0,0) element is the "DC component" as it is often called and is proportional to the mean of the spatial domain image. Go back and read the documentation and you'll see that it really says "Note that F(0,0) is the sum of all the values of f(m,n)." Note that f is the spatial domain image, not the Fourier Transform! The sum of all the values of the image is, of course, proportional to the mean of the image.
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umar siyab
2011년 11월 24일
when u want to centre the image u must use the fftshift function afterall your image will center at f(0,0)... the f(0,0) will contain the lowest values of pixel as compared to move from centre
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