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Having forgotten to commit memory bugs previously. Changes are commited here.

 * Added some empty lines between methods in code and header files.
 *
 * Bugfix: Solved problem in point data saving that the coordinate precision was about 5
 * signs.
 *
 * Sebastian Eichelbaum wrote (18.09.2014, 11:46):
 * >> Hi Andreas
 * >>
 * >> Ich würde dich gern bitten darauf zu achten, dass du zwischen Funktionen
 * >> eine Leerzeile lässt. Das betrifft sowohl die CPP als auch die Header
 * >> files. Als Beispiel: WBmpImage.cpp. Dort hast du nach dem Konstruktor
 * >> eine Leerzeile gemacht, nach dem Destruktor und den folgenden Funktionen
 * >> jedoch nicht.
 * >>
 * >> Ansonsten ist dein Stil sehr sauber. Auch die Doxygen Doku ist sehr
 * >> ordentlich. Super.
 * >>
 * >> Gruß
 * >> Sebastian

 * General style Some style improvements.
 *
 * General features:
 *   - Points - Transform: Color equalizer (contrast and offset setting for each color
 *     channel)
 *
 * Performance improvements (in general about 4 times faster)
 *   - Lari/Habib 2014 clustering has now following improvements.
 *       - Removing points from the parameter space kd-tree after adding to a plane -
 *         This change created an additional, temporary parameter domain kd-tree which
 *         is in the beginning just a copy of the original parameter domain kd-tree.
 *         When points are added to a plane, they are removed from that copy. It makes
 *         the algorithm a way faster.
 *       - Distinguishing whether a point belongs to an extent directly in an point
 *         searcher instance works faster than building a list with additional
 *         unnecessary points and filtering afterwards. In that change a new class
 *         inherited from WPointSearcher and overwrote a method which distinguishes
 *         whether points are added or not.
 *       - Another story is counting points of an extent with a searched point as peak
 *         centre. Previously points were put in a list in order to count them
 *         afterwards. This new class was further modified at traversing. So no new
 *         unnecessary list is built up.
 *
 * Bugs fixed:
 *   - Boundary detection problems were fixed. Originally there was a detection that
 *     checked whether a new bound would hit the pre previously detectet bound. But that
 *     seemet practically not to be enough. So every point adding a new bound is checked
 *     whether it hits one of all bound pieces detected. Nevertheless the problem is not
 *     solved completely but there are much less less problems by far.

 * This approach describes the surface detection of Zahra Lari and Ayman Habib (2014).
 * Paper: "An adaptive approach for the segmentation and extraction of planar
 * andlinear/cylindrical features from laser scanning data", ISPRS Journal of
 * Photogrammetry and Remote Sensing, 2014
 *
 * Eventually the process covers also the linear and cylindrical feature segmentation
 * but in our requirements only the planar segmentation is required. Steps:
 *   - Original laser point cloud as input data
 *   - PCA-based classification of planar features
 *   - Selection of appropriate representation models for the detected planar features
 *   - Local point density estimation along the detected planar features
 *   - Precise estimation of the planar features segmentation attributes
 *   - Parameter-domain segmentation and extraction of planar features
 *   - Boundary tracking for resolving the parameter-domain segmentation ambiguities of
 *     planar features
 *   - Extracted planar features in spatial domain
 *
 * Estimations (Based on the paper because I haven't completely impelemented yet):
 *   - Fair segmentation results
 *   - Relatively slow
 *
 * Implementation progress:
 *   - Done to the step "Precise estimation of the planar features segmentation
 *     attributes".
 *
 *
 * Other updates:
 *   - Renamed module "Pooints - Crop" to "Points - Transform". It optained the feature
 *     to translate and to rotate the point set.
 *   - Wew code refactoring.

Following bugfixes new features:
  - Points group selector plugin: Can output selected buildings as
    WDataSetPointsGrouped in order to be able to view data in other plug-ins
  - Elevation image export plugin: Features to switch elevation display
    in triangle mesh height and color.
  - Fixes in documentation and few code cleanup.

The buildings detection plugin generally was a mix of many things. These things of
it were split up into these plutins:
  - Elevation image export
  - Points group selector which transforms building groups into a voxel structure
    and exports it to a triangle mesh.

Added features:
  - Elevation image can be output in a triangle mesh
  - Elevation image (file and triangle mesh output) and building outline got colored
    building outline

Code style:
  - Fixed prooblems with documentation (make doc)
  - Purged last code style (make stylecheck)

Some simplistic algorithms are done in order to group buildings. Evaluation:
  + Important data structures as Octree and Quadtree are implemented with important functions
  + Grouping neighbor voxels runs even if still not 26-neighborship (few steps required)
     + Algorithm can easily be transferred to the quadtree set.
  + First new plugin for cutting of outlier points using the algorithm that calculates
    figuring out cube connectivity. Other points are cut off that don't belong to the
    largest voxel group
  - Possibly vaporized effort
      - The algorithm that takes relative elevation minimums has problems detecting low buildings.
          - Probably the algorithm won't be taken
          + The great deal of the code amount used for it can be very useful for the final code.
      + It's easy to differ trees from buildings
          - Not thought to the end to differ trees that are very close to buildings

 * This is a first important intermediate step for making sure having a
 * consistent data structure that has an elevation image which has an
 * important role in building detection.