Answers.Body: <p>There was a <a href="https://fips.fi/HDC2021.php" rel="nofollow noreferrer">Helsinki Deblur Challenge 2021</a>, where the goal was to de-blur images of ASCII text. Maybe the submitted networks are suitable also for astronomical pictures. At least the <a href="https://github.com/theophil-trippe/HDC_TUBerlin_version_1" rel="nofollow noreferrer">winner</a> used U-net architecture, as you might guess. Note that here the problem was gray scale, but I guess you can transform the image into (for example) YCbCr color space, de-blur the Y channel and just apply noise filtering to the color channels.</p>
  
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Answers.CreationDate: 2024-06-17T17:53:12.000Z
Answers.Text: Very interesting information, thanks! I assume that it is enough to divide the RGB into three mono layers and get an average PSF, which can already be applied to each layer and end up with a good result.
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Answers.CreationDate: 2024-06-16T20:08:05.947Z
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Body: <p>What modern methods exist for denoising and deblurring images?
  Yes, I haven’t forgotten how to Google and spent a lot of time searching for the code of a neural network that would not have been created 5 years ago, but I didn’t come up with much.
  The idea is to create a modern neural network to remove noise and blur from astronomical images. There are already a couple of options on the market, but they are paid and not available to the average user, or not trained on astronomical data.</p>
  
Tags: <image-processing>
Title: Modern methods for denoising and deblurring images with different image sizes
UserDisplayName: Quark-Coder
ThreadText: # Modern methods for denoising and deblurring images with different image sizes
  
  (Asked by: username_0 on 2024-06-15)
  
  What modern methods exist for denoising and deblurring images?
  Yes, I haven’t forgotten how to Google and spent a lot of time searching for the code of a neural network that would not have been created 5 years ago, but I didn’t come up with much.
  The idea is to create a modern neural network to remove noise and blur from astronomical images. There are already a couple of options on the market, but they are paid and not available to the average user, or not trained on astronomical data.
  
  **Tags:** image-processing
  
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  ## 1 answers
  
  ### Answer by username_1 on 2024-06-16. Score: 1
  
  There was a [Helsinki Deblur Challenge 2021](https://fips.fi/HDC2021.php), where the goal was to de-blur images of ASCII text. Maybe the submitted networks are suitable also for astronomical pictures. At least the [winner](https://github.com/theophil-trippe/HDC_TUBerlin_version_1) used U-net architecture, as you might guess. Note that here the problem was gray scale, but I guess you can transform the image into (for example) YCbCr color space, de-blur the Y channel and just apply noise filtering to the color channels.
  
  > **Comments:**
  > **username_0**: Very interesting information, thanks! I assume that it is enough to divide the RGB into three mono layers and get an average PSF, which can already be applied to each layer and end up with a good result.  
  
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