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  1. Data Management
  2. DM-15636

Investigate DcrCoadd frequency regularization

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      Description

      Frequency regularization in dcrAssembleCoadd.py is designed to suppress positive/negative sidelobes around bright sources, while not zeroing-out the noise. However, the sidelobe suppression leaves some sidelobes in place that I would naively expect to be reduced. These residual sidelobes may be affecting source measurement, and the regularization should be improved.

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          sullivan Ian Sullivan added a comment -

          Please note that this ticket also includes a pull request for pipe_tasks, which no longer shows up in Jira.

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          sullivan Ian Sullivan added a comment - Please note that this ticket also includes a pull request for pipe_tasks, which no longer shows up in Jira.
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          nlust Nate Lust added a comment -

          mostly everything looks good. Random comments to address Ff there were plots you could attach to demonstrate you were able to do what you set out to do, that would be very helpful to review the conceptual part of the algorithm. If it proves very time consuming to do that, it is not strictly necessary.

          Show
          nlust Nate Lust added a comment - mostly everything looks good. Random comments to address Ff there were plots you could attach to demonstrate you were able to do what you set out to do, that would be very helpful to review the conceptual part of the algorithm. If it proves very time consuming to do that, it is not strictly necessary.
          Hide
          sullivan Ian Sullivan added a comment -

          Added two snapshots of DcrCoadds, before and after this change.
          Before:
          https://jira.lsstcorp.org/secure/attachment/34199/BEFORE%20DM-15636.png
          After:
          https://jira.lsstcorp.org/secure/attachment/34198/AFTER%20DM-15636.png

          In each snapshot, a region of the reddest g-band subfilter is shown on the left, and the same subregion of the bluest subfilter on the right. The important detail to notice is that the negative/positive sidelobes see in the "before" images are significantly reduced in the "after" images.

          Show
          sullivan Ian Sullivan added a comment - Added two snapshots of DcrCoadds, before and after this change. Before: https://jira.lsstcorp.org/secure/attachment/34199/BEFORE%20DM-15636.png After: https://jira.lsstcorp.org/secure/attachment/34198/AFTER%20DM-15636.png In each snapshot, a region of the reddest g-band subfilter is shown on the left, and the same subregion of the bluest subfilter on the right. The important detail to notice is that the negative/positive sidelobes see in the "before" images are significantly reduced in the "after" images.
          Hide
          nlust Nate Lust added a comment -

          Some of the stars look significantly rounder (which round stars are usually good) but I wanted to be sure that this modification is ok and expected. It seems to be the smoothing consequence of eroding then dilating the image. Will this smoothing have any implications i.e. will it make it hard to compare to images or something?

          Show
          nlust Nate Lust added a comment - Some of the stars look significantly rounder (which round stars are usually good) but I wanted to be sure that this modification is ok and expected. It seems to be the smoothing consequence of eroding then dilating the image. Will this smoothing have any implications i.e. will it make it hard to compare to images or something?
          Hide
          sullivan Ian Sullivan added a comment -

          To be clear, the erosion and dilation is not operating on the subfilter images, but on boolean arrays that flag whether a given pixel exceeds a threshold. The threshold is relative to the average flux for that pixel across all subfilters, and any clipped pixels are set to that threshold value. So, the erosion and dilation simply ensures that there is a significant cluster of pixels all exceeding the threshold, and each pixel that remains flagged has it's flux set to the average flux in that pixel across al subfilters, times the clamp factor.

          Show
          sullivan Ian Sullivan added a comment - To be clear, the erosion and dilation is not operating on the subfilter images, but on boolean arrays that flag whether a given pixel exceeds a threshold. The threshold is relative to the average flux for that pixel across all subfilters, and any clipped pixels are set to that threshold value. So, the erosion and dilation simply ensures that there is a significant cluster of pixels all exceeding the threshold, and each pixel that remains flagged has it's flux set to the average flux in that pixel across al subfilters, times the clamp factor.
          Hide
          nlust Nate Lust added a comment -

          Thanks, that clears up my understanding of the code significantly! I am fine with you merging what you have anytime you are ready. For my understanding, what makes the stars much rounder is that the sides get evened out the by the averaged pixel value in each image?

          Show
          nlust Nate Lust added a comment - Thanks, that clears up my understanding of the code significantly! I am fine with you merging what you have anytime you are ready. For my understanding, what makes the stars much rounder is that the sides get evened out the by the averaged pixel value in each image?
          Hide
          nlust Nate Lust added a comment -

          A few minor comments, but that was a lot easier to read through. Thank you for all the changes.

          Show
          nlust Nate Lust added a comment - A few minor comments, but that was a lot easier to read through. Thank you for all the changes.

            People

            • Assignee:
              sullivan Ian Sullivan
              Reporter:
              sullivan Ian Sullivan
              Reviewers:
              Nate Lust
              Watchers:
              Ian Sullivan, John Swinbank, Nate Lust
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              Watchers:
              3 Start watching this issue

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