High Pass Filtering: Get It & Sharpen Image

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In summary, using a low-pass filter on a signal and then subtracting it from the original signal results in a high-pass filter. This type of processing highlights the edges of objects and can produce a sharper image in image processing. To achieve an increase in contrast, amplification of the signal is necessary. For a high-pass filter using similar processing, one can use delay and subtract with one delay element and one arithmetic sum or difference. Additional resources on delay and subtract for high-pass filters can be found through further research and learning materials on digital filters.
  • #1
nao113
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Homework Statement
You studied that the delay-and-sum results in low-pass filtering of signal.
How can you realize high-pass filter function using similar processing?

Did I answer them correctly?
Relevant Equations
Theory
How can we get high pass filter? When we apply a low-pass filter to 𝑥 resulting in 𝑦 , then 𝑥−𝑦 should contain whatever is left over, this gives us a high-pass filter. In image processing, high-pass filter will increase the contrast between bright and dark pixel to produce a sharpen image.
 
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  • #2
You are correct about the subtraction.
But your comment on increased contrast is not needed.
A high-pass filter will highlight the edges of objects, but large areas of blacks and whites will become grey, which is not an increase of contrast. To get an increase in contrast, you must amplify the signal.
 
  • #3
Baluncore said:
You are correct about the subtraction.
But your comment on increased contrast is not needed.
A high-pass filter will highlight the edges of objects, but large areas of blacks and whites will become grey, which is not an increase of contrast. To get an increase in contrast, you must amplify the signal.
so, I only need to answer like this `How can we get high pass filter? When we apply a low-pass filter to 𝑥 resulting in 𝑦 , then 𝑥−𝑦 should contain whatever is left over, this gives us a high-pass filter.` right?
 
  • #4
Baluncore said:
You are correct about the subtraction.
But your comment on increased contrast is not needed.
A high-pass filter will highlight the edges of objects, but large areas of blacks and whites will become grey, which is not an increase of contrast. To get an increase in contrast, you must amplify the signal.
And what does it mean by similar processing?
 
  • #5
nao113 said:
And what does it mean by similar processing?
Using one delay element, and one arithmetic sum or difference.
 
  • #6
Baluncore said:
Using one delay element, and one arithmetic sum or difference.
how can I realize High Pass filtering through that process? I think my answer doesn't cover the question.
 
  • #7
nao113 said:
You studied that the delay-and-sum results in low-pass filtering of signal.
How can you realize high-pass filter function using similar processing?
The delay and sum for low-pass is the clue.
For high-pass, you use delay and subtract.
 
  • #8
Baluncore said:
The delay and sum for low-pass is the clue.
For high-pass, you use delay and subtract.
is there any reference for delay and subtract for high pass?
Baluncore said:
The delay and sum for low-pass is the clue.
For high-pass, you use delay and subtract.
Thank you very much for the explanation
 
  • #9
nao113 said:
Homework Statement:: You studied that the delay-and-sum results in low-pass filtering of signal.
How can you realize high-pass filter function using similar processing?

Did I answer them correctly?
Relevant Equations:: Theory

How can we get high pass filter? When we apply a low-pass filter to 𝑥 resulting in 𝑦 , then 𝑥−𝑦 should contain whatever is left over, this gives us a high-pass filter. In image processing, high-pass filter will increase the contrast between bright and dark pixel to produce a sharpen image.
Sorry, are you asking in the context of analog or digital filters? I'm getting the impression that your question is about digital filters, but some of your comments don't make sense to me if so.

nao113 said:
is there any reference for delay and subtract for high pass?
If this is a question for digital filters, what learning resources have you used so far?
 

1. What is a high pass filter?

A high pass filter is a digital image processing technique used to enhance the sharpness and clarity of an image. It works by reducing the low-frequency components of an image, which are responsible for blurring and softening, while preserving the high-frequency components that contain important details and edges.

2. How does a high pass filter sharpen an image?

A high pass filter sharpens an image by removing the low-frequency components, such as smooth areas and gradual transitions, and emphasizing the high-frequency components, such as edges and fine details. This creates a contrast between adjacent pixels, making the image appear sharper and more defined.

3. What are the benefits of using a high pass filter?

The main benefit of using a high pass filter is that it can significantly improve the sharpness and clarity of an image without introducing noise or artifacts. It can also be used to enhance the details and textures in an image, making it more visually appealing and easier to analyze or edit.

4. How do I apply a high pass filter to an image?

To apply a high pass filter to an image, you will need image editing software that supports this feature, such as Adobe Photoshop or GIMP. The exact steps may vary depending on the software, but generally, you will need to duplicate the image layer, apply the high pass filter to the duplicate layer, and then adjust the filter settings to achieve the desired sharpness.

5. Are there any limitations or drawbacks to using a high pass filter?

While a high pass filter can be an effective tool for sharpening images, it is not a one-size-fits-all solution. It may not work well on images with very low contrast or images that are already very sharp. Additionally, overusing the filter can result in a loss of image quality and introduce unwanted artifacts. It is important to use the filter judiciously and adjust the settings carefully to avoid these limitations.

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