FME Transformers: 2024.2

Categories
Point Clouds

Point Clouds

Rasters

Rasters

Related Transformers
PointCloudComponentAdder
PointCloudComponentCopier
PointCloudExpressionEvaluator
PointOnRasterValueExtractor
RasterSelector
Categories
Point Clouds

Point Clouds

Rasters

Rasters

Related Transformers
PointCloudComponentAdder
PointCloudComponentCopier
PointCloudExpressionEvaluator
PointOnRasterValueExtractor
RasterSelector

PointCloudOnRasterComponentSetter

Sets point cloud component values by overlaying a point cloud on a raster. The component values for each point are interpolated from band values at the point location.

Jump to Configuration

Typical Uses

  • Applying color to a point cloud

How does it work?

The PointCloudOnRasterComponentSetter receives two sets of input features, PointCloud and Raster, which must be in the same coordinate system and units.

For each point in the point cloud, component values are set by extracting raster band values from the same location in the underlying raster. These values are interpolated if necessary, and a variety of interpolation methods is available. The extracted values are added to the point’s components as specified - either color (color_red, color_green, color_blue) or a Custom set of components, in which you may select any standard point cloud component to receive raster cell values (including color).

Point cloud features are output with new component values set, and rasters are discarded.

This transformer accepts multiple input point clouds and rasters. One point cloud is output for each input point cloud.

If multiple rasters are used, the component value will be taken from the first raster encountered that can provide one, and so the order of input for rasters can affect the results. If a point does not overlap a raster, the next raster will be tried, and so on until a value is obtained.

Rasters must have the same number of selected bands as there are components selected. For color, three bands are required - red, green and blue. A RasterSelector transformer may be used to meet these conditions - for example, an RGBA raster (color with an additional alpha band) would need to have only its first three bands (RGB) selected to be successfully used with the Components to Set - Color option.

This transformer supports raster band selection. The RasterSelector can be used to modify this selection.

Examples

In this example, we will apply color to a LiDAR point cloud using an orthoimage. As seen here in the FME Data Inspector, the point cloud partially overlaps the underlying orthoimage - the point cloud coverage ends at the shoreline. This view shows an overhead (2D) view of both datasets, the point cloud overlaid on the raster.

Note that the point cloud has a number of standard components, but that does not include color.

Both input features are routed into a PointCloudOnRasterComponentSetter - the point cloud (from LAS format) to the PointCloud input port, and the orthoimage (from MrSID format) to the Raster input port.

In the parameters dialog, we select the Components to Set as Color. Other parameters are left with their default settings.

The output point cloud now has color values in the color_red, color_green, and color_blue components.

Usage Notes

  • The PointCloudOnRasterComponentSetter may be useful to transfer data values when handling non-point cloud data types as point clouds for processing efficiency.

Choosing a Point Cloud Transformer

FME has a selection of transformers for working specifically with point cloud data.

For information on point cloud geometry and properties, see Point Clouds (IFMEPointCloud).

PointCloudCombiner

Combines features into a single point cloud. Point cloud and non-point cloud geometries are supported.

PointCloudComponentAdder

Adds new components with constant values to a point cloud.

PointCloudComponentCopier

Copies selected component values onto either a new or existing component

PointCloudComponentKeeper

Keeps only specified point cloud components, discarding all others.

PointCloudComponentRemover

Removes specified components from a point cloud.

PointCloudComponentRenamer

Renames an existing component.

PointCloudComponentTypeCoercer

Alters the data type of point cloud components, and converts component values if required.

PointCloudConsumer

Reads point cloud features for testing purposes, including any accumulated point cloud operations. No additional operations are performed, and nothing is done with the features.

PointCloudCreator

Creates a point cloud of specified size and density, with default component values.

PointCloudExpressionEvaluator

Evaluates expressions on each point in a point cloud feature, including algebraic operations and conditional statements, and sets individual point cloud component values.

PointCloudExtractor

Serializes the geometry of a point cloud feature into a Blob attribute, encoding the contents according to a choice of common binary point cloud formats.

PointCloudFilter

Separates point clouds into multiple features, based on evaluating expressions including component values, and creates a separate output port for each expression defined.

PointCloudMerger

Merges point clouds by joining points where selected component values match (join key), including x, y, z, and other components. Component values are transferred between point clouds and output is filtered based on matching success and duplication.

PointCloudOnRasterComponentSetter

Sets point cloud component values by overlaying a point cloud on a raster. The component values for each point are interpolated from band values at the point location.

PointCloudPropertyExtractor

Extracts the geometry properties of a point cloud feature and exposes them as attributes, optionally checking for their existence, retrieving component properties, and finding minimum and maximum values. Extents may also be recalculated and updated.

PointCloudReplacer

Decodes a binary attribute containing encoded point clouds stored as Blobs, replacing the feature’s geometry with the decoded point cloud.

PointCloudSimplifier

Reduces the number of points in a point cloud by selectively keeping points based on the shape of the point cloud. The simplified and removed points are output as two discrete point clouds.

PointCloudSorter

Sorts the points within a point cloud by one or more component values.

PointCloudSplitter

Separates point clouds into multiple features based on component values, color, or first/last return.

PointCloudStatisticsCalculator

Calculates statistics on point cloud components and adds the results as attributes.

PointCloudSurfaceBuilder

Takes an input point cloud and reconstructs it into an output mesh.

PointCloudThinner

Reduces the number of points in (thins) a point cloud by keeping points at a fixed interval, a maximum number of points, or a set quantity of first or last points. Remaining points are discarded.

PointCloudToPointCoercer

Converts point clouds to point or multipoint geometries, optionally retaining attribute and component values.

PointCloudTransformationApplier

Applies a point cloud’s scale, offset, or transformation matrix to it, recalculating component values and removing the transformation values.

Configuration

Input Ports

Point cloud features to overlay on the Raster input. Both Raster and PointCloud input should be in the same coordinate system.

Raster(s) from which values will be extracted. Both Raster and PointCloud input should be in the same coordinate system.

Output Ports

Point cloud features with updated component values.

Non-point cloud features will be routed to the <Rejected> port, as well as invalid point clouds.

Rejected features will have an fme_rejection_code attribute with one of the following values:

INVALID_GEOMETRY_TYPE
INVALID_FEATURE_COMPONENTS

Rejected Feature Handling: can be set to either terminate the translation or continue running when it encounters a rejected feature. This setting is available both as a default FME option and as a workspace parameter.

Parameters

Group By

If Group By attributes are selected, features with the same values in the Group By attributes are grouped together, and rasters are only used to set component values of point clouds in the same group.

Complete Groups

Select the point in processing at which groups are processed:

When All Features Received

This is the default behavior. Processing will only occur in this transformer once all input is present.

When Group Changes (Advanced)

This transformer will process input groups in order. Changes of the value of the Group By parameter on the input stream will trigger processing on the currently accumulating group. This may improve overall speed (particularly with multiple, equally-sized groups), but could cause undesired behavior if input groups are not truly ordered.

There are two typical reasons for using When Group Changes (Advanced) . The first is incoming data that is intended to be processed in groups (and is already so ordered). In this case, the structure dictates Group By usage - not performance considerations.

The second possible reason is potential performance gains.

Performance gains are most likely when the data is already sorted (or read using a SQL ORDER BY statement) since less work is required of FME. If the data needs ordering, it can be sorted in the workspace (though the added processing overhead may negate any gains).

Sorting becomes more difficult according to the number of data streams. Multiple streams of data could be almost impossible to sort into the correct order, since all features matching a Group By value need to arrive before any features (of any feature type or dataset) belonging to the next group. In this case, using Group By with When All Features Received may be the equivalent and simpler approach.

Note  Multiple feature types and features from multiple datasets will not generally naturally occur in the correct order.

As with many scenarios, testing different approaches in your workspace with your data is the only definitive way to identify performance gains.

Components to Set

Specifies which point cloud components should be set from the corresponding raster(s).

  • Color specifies that the color_red, color_green, and color_blue components of a point cloud should be set. In this case, the input rasters should have three selected bands.
  • Custom allows specification of an arbitrary list of components, including color.

Components Table

If Components to Set is Custom, select components to be set:

Band

Specifies the band index from which values will be taken.

Band numbering starts at 0 (zero).

Component

The component whose values will be set.

Default Value

The value that will be set for points that are disjoint from all rasters.

Extract Raster Nodata

Specifies the behavior when a point lies on a raster Nodata value.

  • Yes: The point component value will be set to the Nodata value.
  • No: The raster will be skipped, and the next raster checked. If no rasters are found to cover the point, then the Default Values Overwrite Data parameter determines the behavior.

Default Values Overwrite Data

Specifies the behavior when no value can be found for a point from any raster, but the component already existed on the input point cloud.

  • Yes: The component value from the input point cloud will be preserved.
  • No: The component value will be set to the default value, either from the default value list or the FME default.

Interpolation Type

Cell values are interpolated to arrive at point cloud component values. Select an interpolation method for determining values:

Nearest Neighbor

The simplest and fastest method. Values are copied from the nearest cell.

Bilinear

Calculates a weighted average, adjusted for distance, from the four (4) nearest cells.

Bicubic

Calculates a weighted average, adjusted for distance, from the sixteen (16) nearest cells.

Average 4

Calculates a simple average from the four (4) nearest cells.

Similar to Bilinear and is useful for numeric rasters such as DEMs.

Average 16

Calculates a simple average from the sixteen (16) nearest cells.

Similar to Bicubic and is useful for numeric rasters such as DEMs.

Editing Transformer Parameters

Transformer parameters can be set by directly entering values, using expressions, or referencing other elements in the workspace such as attribute values or user parameters. Various editors and context menus are available to assist. To see what is available, click beside the applicable parameter.

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters.

Using the Text Editor

The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.

Text Editor

Using the Arithmetic Editor

The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.

Arithmetic Editor

Conditional Values

Set values depending on one or more test conditions that either pass or fail.

Parameter Condition Definition Dialog

Content

Expressions and strings can include a number of functions, characters, parameters, and more.

When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.

String Functions

These functions manipulate and format strings.

Special Characters

 A set of control characters is available in the Text Editor.

Math Functions

Math functions are available in both editors.
Date/Time Functions Date and time functions are available in the Text Editor.

Math Operators

These operators are available in the Arithmetic Editor.

FME Feature Functions

These return primarily feature-specific values.

FME Parameters

FME and workspace-specific parameters may be used.
Creating and Modifying User Parameters Create your own editable parameters.

Table Tools

Transformers with table-style parameters have additional tools for populating and manipulating values.

Row Reordering

Enabled once you have clicked on a row item. Choices include:

  • Add a row
  • Remove a row
  • Move current row up one
  • Move current row down one
  • Move current row to top
  • Move current row to bottom

Cut, Copy, and Paste

Enabled once you have clicked on a row item. Choices include:

  • Cut a row - delete and copy to clipboard
  • Copy a row to the clipboard
  • Paste a row from the clipboard

Cut, copy, and paste may be used within a transformer, or between transformers.

Filter

Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output.

Import

Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.

Reset/Refresh

Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers.

Note: Not all tools are available in all transformers.

For more information, see Transformer Parameter Menu Options.

Reference

Processing Behavior

Group-Based

Feature Holding

Yes
Dependencies None
Aliases PointCloudOnRasterValueExtractor
History  

FME Community

The FME Community has a wealth of FME knowledge with over 20,000 active members worldwide. Get help with FME, share knowledge, and connect with users globally.

Search for all results about the PointCloudOnRasterComponentSetter on the FME Community.

 

Examples may contain information licensed under the Open Government Licence – Vancouver, Open Government Licence - British Columbia, and/or Open Government Licence – Canada.

Keywords: point "point cloud" cloud PointCloud coerce LiDAR sonar expose extract extents orthophotos PointCloudOnRasterValueExtractor