Make some PCL functions accessible as filters

* Statistical Outlier
* Radius Outlier
* Voxel Grid
* Moving Least Squares
* Grid Projection
* Poisson Surface Reconstruction
* Greedy Projection Triangulation

Enable pngmath extension within Sphinx.

Glob readers, writers, and filters in stage documentation.

doc/conf.py

@@ -25,7 +25,7 @@
 
 # Add any Sphinx extension module names here, as strings. They can be extensions
 # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
-extensions = ['breathe', 'sphinx.ext.autodoc','rst2pdf.pdfbuilder']
+extensions = ['breathe', 'sphinx.ext.autodoc', 'rst2pdf.pdfbuilder', 'sphinx.ext.pngmath']
 
 # Add any paths that contain templates here, relative to this directory.
 # templates_path = ['_templates']
@@ -304,4 +304,3 @@ def read_version(filename):
     'project' : 'api',
     'no-link' : False
 }
-

doc/stages/filters.greedyprojection.rst

@@ -0,0 +1,20 @@
+.. _filters.greedyprojection:
+
+===============================================================================
+filters.greedyprojection
+===============================================================================
+
+The Greedy Projection filter passes data through the Point Cloud Library
+(`PCL`_) GreedyProjectionTriangulation algorithm.
+
+GreedyProjectionTriangulation is an implementation of a greedy triangulation
+algorithm for 3D points based on local 2D projections. It assumes locally smooth
+surfaces and relatively smooth transitions between areas with different point
+densities.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+None at the moment. Relying on defaults within PCL.

doc/stages/filters.gridprojection.rst

@@ -0,0 +1,20 @@
+.. _filters.gridprojection:
+
+===============================================================================
+filters.gridprojection
+===============================================================================
+
+The Grid Projection filter passes data through the Point Cloud Library (`PCL`_)
+GridProjection algorithm.
+
+GridProjection is an implementation of the surface reconstruction method
+described in [Li2010]_.
+
+.. [Li2010] Li, Ruosi, et al. "Polygonizing extremal surfaces with manifold guarantees." Proceedings of the 14th ACM Symposium on Solid and Physical Modeling. ACM, 2010.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+None at the moment. Relying on defaults within PCL.

doc/stages/filters.ground.rst

@@ -0,0 +1,42 @@
+.. _filters.ground:
+
+===============================================================================
+filters.ground
+===============================================================================
+
+The Ground filter passes data through the Point Cloud Library (`PCL`_)
+ProgressiveMorphologicalFilter algorithm.
+
+ProgressiveMorphologicalFilter is an implementation of the method described in
+[Zhang2003]_.
+
+.. [Zhang2003] Zhang, Keqi, et al. "A progressive morphological filter for removing nonground measurements from airborne LIDAR data." Geoscience and Remote Sensing, IEEE Transactions on 41.4 (2003): 872-882.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+maxWindowSize
+  Maximum window size. [Default: **33**]
+
+slope
+  Slope. [Default: **1.0**]
+
+maxDistance
+  Maximum distance. [Default: **2.5**]
+
+initialDistance
+  Initial distance. [Default: **0.15**]
+
+cellSize
+  Cell Size. [Default: **1**]
+
+classify
+  Apply classification labels? [Default: **true**]
+
+extract
+  Extract ground returns? [Default: **false**]
+
+approximate
+  Use approximate algorithm? [Default:: **false**]

doc/stages/filters.movingleastsquares.rst

@@ -0,0 +1,22 @@
+.. _filters.movingleastsquares:
+
+===============================================================================
+filters.movingleastsquares
+===============================================================================
+
+The Moving Least Squares filter passes data through the Point Cloud Library
+(`PCL`_) MovingLeastSquares algorithm.
+
+MovingLeastSquares is an implementation of the MLS (Moving Least Squares)
+algorithm for data smoothing and improved normal estimation described in
+[Alexa2003]_. It also contains methods for upsampling the resulting cloud based
+on the parametric fit.
+
+.. [Alexa2003] Alexa, Marc, et al. "Computing and rendering point set surfaces." Visualization and Computer Graphics, IEEE Transactions on 9.1 (2003): 3-15.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+None at the moment. Relying on defaults within PCL.

doc/stages/filters.poisson.rst

@@ -0,0 +1,23 @@
+.. _filters.poisson:
+
+===============================================================================
+filters.poisson
+===============================================================================
+
+The Poisson filter passes data through the Point Cloud Library (`PCL`_) Poisson
+surface reconstruction algorithm.
+
+Poisson is an implementation of the method described in [Kazhdan2006]_.
+
+.. [Kazhdan2006] Kazhdan, Michael, Matthew Bolitho, and Hugues Hoppe. "Poisson surface reconstruction." Proceedings of the fourth Eurographics symposium on Geometry processing. Vol. 7. 2006.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+depth
+  Maximum depth of the tree used for reconstruction. [Default: **8**]
+
+pointWeight
+  Importance of interpolation of point samples in the screened Poisson equation. [Default: **4.0**]

doc/stages/filters.radiusoutlier.rst

@@ -0,0 +1,31 @@
+.. _filters.radiusoutlier:
+
+===============================================================================
+filters.radiusoutlier
+===============================================================================
+
+The Radius Outlier filter passes data through the Point Cloud Library (`PCL`_)
+RadiusOutlierRemoval algorithm.
+
+RadiusOutlierRemoval filters points in a cloud based on the number of neighbors
+they have. Iterates through the entire input once, and for each point, retrieves
+the number of neighbors within a certain radius. The point will be considered an
+outlier if it has too few neighbors, as determined by ``min_neighbors``. The
+radius can be changed using ``radius``.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+min_neighbors
+  Minimum number of neighbors in radius. [Default: **2**]
+
+radius
+  Radius. [Default: **1.0**]
+
+classify
+  Apply classification labels? [Default: **true**]
+
+extract
+  Extract ground returns? [Default: **false**]

doc/stages/filters.statisticaloutlier.rst

@@ -0,0 +1,40 @@
+.. _filters.statisticaloutlier:
+
+===============================================================================
+filters.statisticaloutlier
+===============================================================================
+
+The Statistical Outlier filter passes data through the Point Cloud Library
+(`PCL`_) StatisticalOutlierRemoval algorithm.
+
+StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier
+data. The algorithm iterates through the entire input twice. During the first
+iteration it will compute the average distance that each point has to its
+nearest k neighbors. The value of k can be set using ``mean_k``. Next, the mean
+and standard deviation of all these distances are computed in order to determine
+a distance threshold. The distance threshold will be equal to:
+:math:`mean + stddev_mult * stddev`. The multiplier for the standard deviation
+can be set using ``multiplier``. During the next iteration the points will be
+classified as inlier or outlier if their average neighbor distance is below or
+above this threshold respectively.
+
+See [Rusu2008]_ for more information.
+
+.. [Rusu2008] Rusu, Radu Bogdan, et al. "Towards 3D point cloud based object maps for household environments." Robotics and Autonomous Systems 56.11 (2008): 927-941.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+mean_k
+  Mean number of neighbors. [Default: **2**]
+
+multiplier
+  Standard deviation threshold. [Default: **0.0**]
+
+classify
+  Apply classification labels? [Default: **true**]
+
+extract
+  Extract ground returns? [Default: **false**]

doc/stages/filters.voxelgrid.rst

@@ -0,0 +1,30 @@
+.. _filters.voxelgrid:
+
+===============================================================================
+filters.voxelgrid
+===============================================================================
+
+The Voxel Grid filter passes data through the Point Cloud Library (`PCL`_)
+VoxelGrid algorithm.
+
+VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples +
+filters the data. The VoxelGrid class creates a *3D voxel grid* (think about a
+voxel grid as a set of tiny 3D boxes in space) over the input point cloud data.
+Then, in each *voxel* (i.e., 3D box), all the points present will be
+approximated (i.e., *downsampled*) with their centroid. This approach is a bit
+slower than approximating them with the center of the voxel, but it represents
+the underlying surface more accurately.
+
+.. _`PCL`: http://www.pointclouds.org
+
+Options
+-------------------------------------------------------------------------------
+
+leaf_x
+  Leaf size in X dimension. [Default: **1.0**]
+
+leaf_y
+  Leaf size in Y dimension. [Default: **1.0**]
+
+leaf_z
+  Leaf size in Z dimension. [Default: **1.0**]

doc/stages/index.rst

@@ -10,65 +10,24 @@ Readers
 
 .. toctree::
    :maxdepth: 1
+   :glob:
 
-   readers.buffer
-   readers.faux
-   readers.geowave
-   readers.greyhound
-   readers.las
-   readers.mrsid
-   readers.nitf
-   readers.oci
-   readers.optech
-   readers.pcd
-   readers.pgpointcloud
-   readers.ply
-   readers.qfit
-   readers.rxp
-   readers.sbet
-   readers.sqlite
+   readers.*
 
 Writers
 =======
 
 .. toctree::
    :maxdepth: 1
+   :glob:
 
-   writers.derivative
-   writers.geowave
-   writers.las
-   writers.matlab
-   writers.nitf
-   writers.oci
-   writers.ply
-   writers.p2g
-   writers.pcd
-   writers.pgpointcloud
-   writers.pclvisualizer
-   writers.rialto
-   writers.sqlite
-   writers.text
+   writers.*
 
 Filters
 =======
 
 .. toctree::
    :maxdepth: 1
+   :glob:
 
-   filters.attribute
-   filters.colorization
-   filters.chipper
-   filters.crop
-   filters.decimation
-   filters.ferry
-   filters.hexbin
-   filters.mortonorder
-   filters.merge
-   filters.pclblock
-   filters.predicate
-   filters.programmable
-   filters.range
-   filters.reprojection
-   filters.sort
-   filters.stats
-   filters.transformation
+   filters.*

plugins/pcl/CMakeLists.txt

@@ -131,6 +131,34 @@ PDAL_ADD_PLUGIN(ground_filter_libname filter ground
     FILES filters/GroundFilter.hpp filters/GroundFilter.cpp
     LINK_WITH ${PCL_LIBRARIES})
 
+PDAL_ADD_PLUGIN(statistical_outlier_filter_libname filter statisticaloutlier
+    FILES filters/StatisticalOutlierFilter.hpp filters/StatisticalOutlierFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(radius_outlier_filter_libname filter radiusoutlier
+    FILES filters/RadiusOutlierFilter.hpp filters/RadiusOutlierFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(voxelgrid_filter_libname filter voxelgrid
+    FILES filters/VoxelGridFilter.hpp filters/VoxelGridFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(movingleastsquares_filter_libname filter movingleastsquares
+    FILES filters/MovingLeastSquaresFilter.hpp filters/MovingLeastSquaresFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(gridprojection_filter_libname filter gridprojection
+    FILES filters/GridProjectionFilter.hpp filters/GridProjectionFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(poisson_filter_libname filter poisson
+    FILES filters/PoissonFilter.hpp filters/PoissonFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
+PDAL_ADD_PLUGIN(greedyprojection_filter_libname filter greedyprojection
+    FILES filters/GreedyProjectionFilter.hpp filters/GreedyProjectionFilter.cpp
+    LINK_WITH ${PCL_LIBRARIES})
+
 #
 # PCL Kernel
 #