Uncovering the Blurred Image: Finding K & f

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In summary, the conversation discussed the problem of finding the transformation (K) and noise (f) in a blurred image represented by the equation A=Ku+f. The question was how to find K and f when blurring an image, specifically using gaussian blurring. The suggested solution was to use a regularization approach, as explained in the linked source.
  • #1
sigh1342
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Homework Statement


I found that the blurred image is always presented by
$$A=Ku+f$$, where u is the perfect image source, and the K is transformation (blurring, sampling)
and f is the noising . The question I want to know is how can we find such K, or f when we blurred the image , for example ,using the gaussian blurring.
In other word, I want to know how can I find K or f s.t. I can do the same effect as using the
imnoise function in MATLAB as gaussian blurring or ...


Homework Equations


I found that there are matrix related to it, where the matrix is given by h=fspecial('gaussian',256);
and it is all zeros.


The Attempt at a Solution

 
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  • #2
It's an inverse problem ... you need to use some regularization approach.
http://home.comcast.net/~szemengtan/InverseProblems/chap3.pdf
 
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  • #3
um,, I just want to know how can I find such K and f...
Thanks you.:)
 
  • #4
And I told you - use a regularization technique.
I'm not going to write out the 10-20 pages of theory here - hence the link.
 

1. What is the purpose of uncovering blurred images?

The purpose of uncovering blurred images is to improve the quality and clarity of the image. Blurring can occur due to various factors such as camera shake, motion blur, or defocusing. By finding the correct values for K and f, we can effectively deblur the image and make it more visually appealing.

2. What is K and how does it affect image blurring?

K, also known as the blur kernel, is a mathematical representation of the blurring process. It describes the path of light from a point in the scene to a point in the image. The size and shape of K determines the amount and direction of blurring in the image.

3. What is f and how does it affect image blurring?

f, also known as the point spread function, is a measure of the blur radius in the image. It represents the distance from the center of the image to the edge of the blur. The larger the f value, the more blurred the image will be.

4. How do we determine the values of K and f?

The values of K and f can be determined through various techniques such as blind deconvolution, which is an iterative process of estimating the blur kernel and point spread function. Other methods include using known patterns or objects in the image to estimate the blur parameters.

5. Can we completely remove blurring from an image?

No, it is not possible to completely remove blurring from an image. The blurring process is irreversible, meaning that some information is lost during the blur. However, by finding the correct values of K and f, we can significantly reduce the blurring and improve the quality of the image.

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