Merge remote-tracking branch 'origin/master' into gdal-metadata

doc/stages/filters.optimalneighborhood.rst

@@ -44,4 +44,4 @@ min_k
 
 max_k
   The maximum number of k nearest neighbors to consider for optimal
-  neighborhood selection. [Default: 100]
+  neighborhood selection. [Default: 14]

doc/stages/filters.transformation.rst

@@ -3,12 +3,9 @@
 filters.transformation
 ======================
 
-The transformation filter applies an arbitrary rotation+translation
+The transformation filter applies an arbitrary homography
 transformation, represented as a 4x4 matrix_, to each xyz triplet.
 
-The filter does *no* checking to ensure the matrix is a valid affine
-transformation.
-
 .. note::
 
     The transformation filter does not apply or consider any spatial
@@ -59,10 +56,11 @@ A full tutorial about transformation matrices is beyond the scope of this
 documentation. Instead, we will provide a few pointers to introduce core
 concepts, especially as pertains to PDAL's handling of the ``matrix`` argument.
 
-Transformations in a 3-dimensional coordinate system can be represented as an
-affine transformation using homogeneous coordinates. This 4x4 matrix can
-represent transformations describing operations like translation, rotation, and
-scaling of coordinates.
+Transformations in a 3-dimensional coordinate system can be represented
+as a homography transformation using homogeneous coordinates. This 4x4
+matrix can represent affine transformations describing operations like
+translation, rotation, and scaling of coordinates.  In addition it can
+represent perspective transformations modeling a pinhole camera.
 
 The transformation filter's ``matrix`` argument is a space delimited, 16
 element string. This string is simply a row-major representation of the 4x4

filters/TransformationFilter.cpp

@@ -190,15 +190,16 @@ bool TransformationFilter::processOne(PointRef& point)
     double x = point.getFieldAs<double>(Dimension::Id::X);
     double y = point.getFieldAs<double>(Dimension::Id::Y);
     double z = point.getFieldAs<double>(Dimension::Id::Z);
+    double s = x * matrix[12] + y * matrix[13] + z * matrix[14] + matrix[15];
 
     point.setField(Dimension::Id::X,
-        x * matrix[0] + y * matrix[1] + z * matrix[2] + matrix[3]);
+       (x * matrix[0] + y * matrix[1] + z * matrix[2] + matrix[3]) / s);
 
     point.setField(Dimension::Id::Y,
-        x * matrix[4] + y * matrix[5] + z * matrix[6] + matrix[7]);
+       (x * matrix[4] + y * matrix[5] + z * matrix[6] + matrix[7]) / s);
 
     point.setField(Dimension::Id::Z,
-        x * matrix[8] + y * matrix[9] + z * matrix[10] + matrix[11]);
+       (x * matrix[8] + y * matrix[9] + z * matrix[10] + matrix[11]) / s);
     return true;
 }