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Add quadratic average sampling method to overview computation #1553

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mgoacolou
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What does this PR do?

This add a new average algorithm witch, for SAR product make more visible small brillant object in high level overviews

What are related issues/pull requests?

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  • ADD YOUR TASKS HERE
  • Add test case(s)
  • Review
  • Adjust for comments
  • All CI builds and checks have passed

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gdal/gcore/overview.cpp Outdated Show resolved Hide resolved
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@mloskot mloskot changed the title add quadratic average to overview computation Add quadratic average sampling method to overview computation May 22, 2019
@rouault
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rouault commented Aug 11, 2019

Sorry I somehow missed this pull request. Could you add a test case for the new method in autotest/gcore/tiff_ovr.py for example ?
Regarding the complex number case, pardon my ignorance, I was wondering if there's really some "physical" significance in the real & imaginary part of the results. I mean the maths looks right, but what is the interpretation of that number ? Wouldn't for example the quadratic average of the modulus of the numbers be something more natural ? Even in the real case, the quadratic average of a set of negative numbers is a positive one

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rouault commented Oct 10, 2019

@mgoacolou ping regarding my questions in #1553 (comment)

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stale bot commented Jan 30, 2020

The GDAL project highly values your contribution and would love to see this work merged! Unfortunately this PR has not had any activity in the last 21 days and is being automatically marked as "stale". If you think this pull request should be merged, please check - that all unit tests are passing - that all comments by reviewers have been addressed - that there is enough information for reviewers, in particular

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@stale stale bot added the stale label Jan 30, 2020
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stale bot commented Feb 6, 2020

While we hate to see this happen, this PR has been automatically closed because it has not had any activity in the last 28 days. If this pull request should be reconsidered, please follow the guidelines in the previous comment and reopen this pull request. Or, if you have any further questions, just ask! We love to help, and if there's anything the GDAL project can do to help push this PR forward please let us know how we can assist.

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3 participants