[pdal-commits] [PDAL/PDAL] 8a2249: Add Extended Local Maximum (ELM) filter

[GitHub]

  Branch: refs/heads/release-ready
  Home:   https://github.com/PDAL/PDAL
  Commit: 8a22494cf4dd17f9cbac85829edc7c60342b7b48
      https://github.com/PDAL/PDAL/commit/8a22494cf4dd17f9cbac85829edc7c60342b7b48
  Author: Howard Butler <howard at hobu.co>
  Date:   2017-04-06 (Thu, 06 Apr 2017)

  Changed paths:
    M doc/references.rst
    A doc/stages/filters.elm.rst
    A filters/ELMFilter.cpp
    A filters/ELMFilter.hpp
    M pdal/StageFactory.cpp

  Log Message:
  -----------
  Add Extended Local Maximum (ELM) filter

Based off the work of Chen, et al. In the original work, the authors used ELM
to generate grid minimums that were resistent to low outliers in ground
segmentation and DTM generation. We implement here as a standalone filter that
simply marks the low points as noise. Downstream filtering stages can ignore,
extract, or handle these noise points as they see fit.


  Commit: 8e22916871d2d0c7ed81f4b35ecba65371a36250
      https://github.com/PDAL/PDAL/commit/8e22916871d2d0c7ed81f4b35ecba65371a36250
  Author: Howard Butler <howard at hobu.co>
  Date:   2017-04-06 (Thu, 06 Apr 2017)

  Changed paths:
    M io/LasReader.cpp
    M test/unit/io/LasReaderTest.cpp

  Log Message:
  -----------
  Squashed commit of the following:

commit f7a56630d3c37ec6cf080cad0a7b1759cfa79bdc
Author: Connor Manning <connormanning at users.noreply.github.com>
Date:   Thu Apr 6 08:55:01 2017 -0500

    Preserve well-known, but non-standard to LAS, dimension IDs when written as extra_dims. (#1555)

commit eb1e3ff9fc3fd65a55b5075d5fc388e9cd111eff
Merge: effed6214 c9216dfdd
Author: chambbj <brad.chambers at gmail.com>
Date:   Thu Apr 6 08:15:13 2017 -0400

    Merge pull request #1554 from PDAL/add-elm-filter

    Add Extended Local Maximum (ELM) filter

commit c9216dfdd07f6c316130318628a1ba9df1695fdd
Author: Bradley J Chambers <brad.chambers at gmail.com>
Date:   Wed Apr 5 16:22:42 2017 -0400

    Add Extended Local Maximum (ELM) filter

    Based off the work of Chen, et al. In the original work, the authors used ELM
    to generate grid minimums that were resistent to low outliers in ground
    segmentation and DTM generation. We implement here as a standalone filter that
    simply marks the low points as noise. Downstream filtering stages can ignore,
    extract, or handle these noise points as they see fit.


Compare: https://github.com/PDAL/PDAL/compare/f09cf4e2ce4a...8e22916871d2