Solving Image Processing Problem: Fourier Transform and Image Dimensions

In summary, the conversation discusses the Fourier transform of an image and how it relates to a new image with twice the dimensions. The correct solution is to interpolate the extra points between the original points, known as zero-padding. However, this solution only works for even values of x and y, and needs to be interpolated for odd values.
  • #1
mr_k
9
0
hi!
i need help with problem:
Let F(u,v) be the Fourier transform of an M x N image f(x,y). Let g(x,y) be an image of dimensions (2 M) x (2 N) whose Fourier transform G(u,v) is defined as follows:
quest2.gif

What does the image g(x,y) look like in terms of f(x,y)?

my solution : g(x,y)=0.25f(x/2,y/2).

Is that true?

thanks :)
 
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  • #2
No, you're on the wrong track. You have an image that has looks basically the same but has twice (in this case) as many points. These extra points are interpolated between the points of the original f. This is known as zero-padding. See if you can work it out from the DFT expressions.
 
  • #3
You are not completely on the wrong track, but your math solution is wrong, because the functions f(x,y) etc are only defined when x and y are integers. You can't talk about "half a pixel", so f(x/2, y/2) doesn't mean anything if x or y are odd numbers.

On the other hand if you say what your formula means "in words" rather than as a math formula, it does describe what the image "looks like".
 
  • #5
mr_k said:
hi,my solution:

What's the problem with the answer?

thanks.

Your answer is fine for even x and y.
But what happens if x or y is odd?
 
  • #6
ok,So what's the right answer?
 
  • #7
Your answer is right, but you should add that if x or y is odd, that the value is effectively interpolated.
 
  • #8
thanks!
 

What is image processing problem?

Image processing problem refers to the challenges and obstacles in manipulating and analyzing digital images using computer algorithms. This can include tasks such as image enhancement, restoration, segmentation, and interpretation.

What are the applications of image processing?

Image processing has a wide range of applications in various industries such as healthcare, surveillance, entertainment, and manufacturing. It is used for tasks such as medical imaging, object recognition, video editing, and quality control in manufacturing.

What are the common techniques used in image processing?

Some common techniques used in image processing are image filtering, edge detection, image segmentation, and morphological operations. These techniques involve manipulating pixels in an image to achieve a desired result.

What are the challenges in image processing?

Image processing can face challenges such as noise, low contrast, and artifacts in the image. These can affect the accuracy and effectiveness of algorithms and can require additional preprocessing steps to overcome.

What skills are required for image processing?

Proficiency in programming languages such as Python or MATLAB, knowledge of image processing libraries and tools, understanding of mathematical concepts such as linear algebra and signal processing, and critical thinking and problem-solving skills are some key skills required for image processing.

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