How to compute the 2D inverse Fourier transform?

In summary, the problem is to obtain the inverse Fourier transform of a 2D function, with relevant equations and a suggested method of using polar coordinates.
  • #1
bgturk
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0

Homework Statement



The problem is to obtain the inverse Fourier transform of the following 2D functions

[tex]F(\mathbf{k})=\frac{k_{x}k_{y}}{k^{2}}[/tex]

Homework Equations



The relevant equations are the 2d Fourier transform formulas described http://fourier.eng.hmc.edu/e101/lectures/Image_Processing/node6.html" .

The Attempt at a Solution



[tex]\int d^{2}\mathbf{k}\,\frac{k_{x}k_{y}}{k^{2}}e^{i\mathbf{k}\cdot\mathbf{r}}&=&\int_{-\infty}^{+\infty}dp\int_{-\infty}^{+\infty}dq\,\frac{p q}{p^{2}+q^{2}}e^{ipx+iqy}[/tex]

How would you proceed with the evaluation of this integral? I need some guidance on how to compute integrals like the above.
 
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  • #2
could you try polar co-ords?
 

Related to How to compute the 2D inverse Fourier transform?

1. What is the purpose of computing the 2D inverse Fourier transform?

The 2D inverse Fourier transform is used to convert a signal or image from the frequency domain back to the spatial or time domain. This allows for the analysis and manipulation of data in its original form, rather than in the frequency domain which can be difficult to interpret.

2. How is the 2D inverse Fourier transform calculated?

The 2D inverse Fourier transform is calculated by taking the complex conjugate of the 2D Fourier transform and dividing it by the total number of pixels in the image. This operation is performed on each pixel in the image, resulting in a reconstructed version of the original image.

3. What is the relationship between the 2D Fourier transform and the 2D inverse Fourier transform?

The 2D Fourier transform and the 2D inverse Fourier transform are inverse operations of each other. This means that applying the 2D Fourier transform to an image and then applying the 2D inverse Fourier transform to the resulting image will return the original image.

4. How does the 2D inverse Fourier transform affect image quality?

The 2D inverse Fourier transform can improve image quality by removing high-frequency noise from the image. This is because high-frequency components in an image are represented by complex numbers in the frequency domain, and taking the complex conjugate during the inverse transform effectively removes these components.

5. Are there any limitations to using the 2D inverse Fourier transform?

One limitation of the 2D inverse Fourier transform is that it assumes the input signal or image is periodic, meaning it repeats infinitely in all directions. In reality, most signals and images are not truly periodic, so there may be some error in the reconstruction. Additionally, the 2D inverse Fourier transform is computationally intensive and may not be practical for large or complex images.

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