Densify

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Point cloud

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Mesh

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DSM

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Orthomosaic

PIX4Dmatic_point_cloud_icon_small.png Densify PIX4Dmatic_depth_point_cloud_small.png Depth point cloud PIX4Dmatic_fusion_depth_dense_small.png Depth & dense fusion

Densify

The Densify step generated a dense point cloud from images.

 
Access: 
  • Click Process processing_options.png.
  • On the Menu bar, click Process > Densify...

It allows users to change the following processing options:

Algorithm

This option allows switching between the densification algorithms:

  • HW accelerated (Default): The densification will be computed using a GPU-capable algorithm. This option can contribute to reduced processing time.
  • Standard: The densification will be computed using the standard algorithm.
 
Note: The HW accelerated algorithm is automatically selected if a compatible GPU is installed (any NVIDIA GPU that supports OpenGL 4.1 or higher). Check here on How to verify the supported OpenGL versions of the graphics card.
 
Note: The HW accelerated algorithm was tested on Windows 10 and we compared it to the Standard algorithm. The tests showed that the densification processing time is on average 52% faster using the HW accelerated algorithm compared it to the Standard algorithm. We also report a slight increase in the number of densified points.

Image scale

Image Scale defines the scale of the images at which additional 3D points are computed.

  • 1/1 (Original image size, Slow): The original image size is used to compute additional 3D points. This option require four times more RAM and processing time than when processing with the default value 1/2, and usually it does not significantly improve results.
  • 1/2 (Half image size, Default): Half size images are used to compute additional 3D points. It is the recommended image scale.
  • 1/4 (Quarter image size, Fast): Quarter size images are used to compute additional 3D points. Less points are computed than with the 1/2 image scale and the processing time is reduced. This option can generate more points when processing vegetation areas.
  • 1/8 (Eighth image size, Tolerant): Eighth size images are used to compute additional 3D points. Less points are computed than with the 1/2 or 1/4 image scale and the processing time is further reduced. This option can generate more points when processing vegetation areas.

Multiscale

Multiscale (default): When this option is activated, additional 3D points are computed on multiple image scales, starting with the selected Image scale and going to the 1/8 image scale.

 
Example: If 1/2 image scale is selected, additional points are computed on images with 1/2, 1/4, and 1/8 image scale.
 
Tip: We recommend to enable the Multiscale option when:
  • Computing additional points in vegetation areas as well as keeping details in areas without vegetation.
  • Filling holes in places with low texture, for example, uniform walls.
The Multiscale option may generate additional noise, we recommend to disable the Multiscale option when:
  • The edges of buildings contain noise.
  • When reconstructing thin elements, for example, the structure of the cell tower.

Density

This parameter defines the density of the point cloud:

  • Optimal (Default): A 3D point is computed for every 8th pixel of the original image. This is the recommended point cloud density.
  • High: A 3D point is computed for every 2nd pixel of the original image. It results in an oversampled point cloud that requires up to 4 times more processing time and RAM than Optimal density. Typically, this point cloud option does not significantly improve the results compared to Optimal density.
  • Low: A 3D point is computed for every 32nd pixel of the original image. The final point cloud is computed up to 4 times faster and uses up to 4 times less RAM than Optimal density.
 
Note: The point Density has an impact on the processing time and the number of 3D points generated.

Minumum matches

Minimum Number of Matches (2-6, 3 default) represents the minimum number of valid re-projections of this 3D point to the images. For example, when using the Minimum Number of Matches 3 (default), each 3D point has to be correctly re-projected in at least 3 images.

 
Tip: We recommend using the Minimum Number of Matches:
  • 2: For projects with a small overlap. Note that this option produces a point cloud with more noise and artifacts.
  • 4, 5, or 6: To reduce the noise and improve the quality of the point cloud. Note that this option might compute less 3D points in the final point cloud.

Noise filter

Noise filter processing option provides a cleaner point clouds for datasets with oblique images.

It filters out points that are generated far away from images for example, features that are visible on images but are far on the horizon will not be reconstructed. 

 
Example: When the Noise filter is enabled for a cell tower project, points that are far away from the images do not get reconstructed.

PIX4Dmatic_noise_filter_enabled

Noise filter - enabled.

PIX4Dmatic_noise_filter_disabled

Noise filter - disabled.

Sky filter

Sky filter processing option removes points in a dense point cloud associated with sky

The feature is especially useful for datasets that contain sky in images, for example:

  • Terrestrial datasets acquired with PIX4Dcatch.
  • Inspection datasets acquired with PIX4Dscan. 

PIX4Dmatic sky filter

Using the Sky filter processing option automatically removes points that represent sky.

 
Important: The Sky filter processing option significantly increases the processing time. We recommend using it only for datasets that contain a lot of sky in images.

Exports

To export the point cloud automatically during the Densify step:

  • In Exports, select the Dense point cloud .las option.
  • (Optional) Click Pix4Dmatic_folder.png and specify the desired path and filename.
 
Note: The Dense point cloud .las option is disabled by default. It is possible to export the point cloud without re-running Densify step:
  • On the Menu tab, click File > Export dense point cloud .las...
  • Specify the desired path and filename.
  • Click Save.

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