Local Normalization with Normalized Scale Gradient?

I have data that would benefit from local normalization, but I'd also like to use the NSG script to ensure proper image weighting.  Doing so typically requires that we select "No Normalization" in the ImageIntegration process.  This seems to make it impossible to perform both Local Normalization (which requires that we select "Local Normalization") and NSG on a set of data before integration.  So how does one take advantage of Local Normalization and at the same time ensure proper image weighting?

Best,
Aaron

Comments

  • You know...I was about to answer...but I think I should let @JohnMurphy really speak to this. 
    My gut says you will not want to mix-and-match the normalization and weighting aspects of what will be image integration. I think you are going to have to pick (though I could definitely be wrong.)

    -the Blockhead
  • With the current version of NSG, you would need to:
    1. Use NSG to normalize the data. Set the Gradient smoothness to maximum smoothness (4.0). The results will be corrected for the average image brightness scale, and the best fit linear gradient.
    2. Use the NSG output files as the input to Local Normalization.
    3. In ImageIntegration, set Normalization to Local normalization, Weights to FITS keyword and the Weight keyword to NWEIGHT
    What image problems are you trying to solve? I would expect NSG to do a better job than Local Normalization in almost all circumstances.

    Regards, John Murphy
  • Thanks a lot for this.  Just trying to remove some gradients from my Oiii subs, but I think using NSG and then DBE basically took care of it.  Thanks again!

    Best,
    Aaron
    (PI newbie)
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