Content Comparison

VisionLidar offers multiple display modes to visualize point cloud data, depending on the available information. These options can be accessed in the “View” menu under the first section.

Available Display Modes

Color by RGB

• Displays points

with their

• using color

issued

• data from the source file

. Usually produced from a captured image. RGB values from an image taken by the scanner are often interpolated, therefore not as precise as the intensity and may show oddities such as cars or leaves on walls.

• Color by intensity: Intensity is the measure of the laser signal return strength for each point. It is shown as a grayscale from 0 to 254.  This method produces a rendering which is much like a black and white photo, but which is also much closer to reality than the RGB rendering, due to its nature. There is an option in the setting allowing to change the minimum and maximum value of the greyscale, adjusting the view for point clouds that are too dark or bright.

• Color by class: Displays points by their class value. A list of classes is available in the explorer in the “Classes” tab. The points may have already been classified in some way; some data comes already classified through standard classifications from aerial survey. The user can decide to view or not each class, change the title of the class and specify a display color in the explorer.  At times, the point cloud is not classified, in such case all points will be considered unclassified class “0” or “1”.  It will also be possible to use the algorithms available with VisionLidar in order to classify the point clouds (see Classification Algorithms section). 

• Color by normals: This option colors points differently whether they are on horizontal planes or vertical planes. The normals must be calculated beforehand otherwise the point cloud will only be displayed with a uniform colour. (Menu: Analyze / Compute Normals).

• Color by scan: Displays each source file with assorted color tones, which can be chosen in the explorer (see the “Scans” tab in the explorer). The tone also shows the intensity values. The list of scans in the explorer can be used to hide selected scans or translate and rotate them individually.

• Color by elevation: Displays the point cloud according to the elevation of the points.

Color by distance: Displays the point cloud according to the distance from a given plane

• , typically derived from captured images.

• Important Considerations:

  • RGB values from scanner images are often interpolated and may lack precision.

  • Objects like cars or leaves may appear on vertical surfaces due to image mapping artifacts.

Color by Intensity

• Uses grayscale values (0 to 254) to represent the laser return strength of each point.

• Provides a realistic, black-and-white rendering, often more accurate than RGB visualization.

• Adjustable grayscale range settings are available to enhance visibility for point clouds that appear too dark or too bright.

Color by Class

• Displays points based on classification values (e.g., ground, buildings, vegetation).

• The Classes tab in the Explorer allows users to:

  • Show or hide specific classes.

  • Rename class titles.

  • Assign custom display colors.

• Some point clouds come pre-classified, particularly those from aerial surveys.

• Unclassified points are typically assigned to Class 0 or 1.

Color by Normals

• Differentiates points based on their orientation:

  • Horizontal surfaces appear in one color.

  • Vertical surfaces appear in another.

• Normals must be computed first (Menu: /wiki/spaces/VisionLidarEN17/pages/2785615) for this display mode to work.

• If normals are not calculated, the entire point cloud will display in a uniform color.

Color by Scan

• Assigns distinct colors to points based on their source file.

• The Scans tab in the Explorer allows users to:

  • Change the color tone of individual scans.

  • Show or hide specific scans.

  • Translate and rotate scans individually.

• Also retains intensity values within the color scheme.

Color by Elevation

• Colors the point cloud based on point height (Z-axis elevation).

• Useful for topographic analysis and terrain modeling.

Color by Distance

• Colors points according to their distance from a given plane.

• Helps visualize relative depth and spatial variations within the dataset.