Configuration for Imaging Parameters of RadarImager#
taskImaging#
The imaging section provides all necessary parameters to select the relevant data from the recorded data to generate an image (stack).
Using the layerSelection.indexedPositions parameter
allows selection of the layer of the recorded data to be displayed in the image.
The transpose and flip nodes contains parameters that allow to manipulate the orientation of the image.
This can be useful to align the image with the physical orientation of the object being measured.
By combining all these nodes, it is possible to display any image orientation.
The normalAbs parameters define how the captured data is normalized and scaled to generate the image.
The generated data is normalized into an 8-bit integer range for efficiency and compatibility with standard image formats.
Depending on the application, the scaling of the data can be adjusted to highlight specific features within the 8-bit integer range.
Additionally, the logScale parameter enables logarithmic scaling for the normalization of image data.
When enabled, this parameter applies a logarithmic transformation with parameterizable dynamics
to the data before normalization, which can be useful for enhancing the visibility of features with a wide dynamic range.
This is particularly beneficial for highlighting subtle variations in the image data that might be less noticeable with linear scaling.
layerSelection.indexedPositions#
This parameter allows selection of the layer of the recorded data to be displayed in the image. The layer index corresponds to a specific distance from the RadarImager (z-axis).
The layer with index 0 corresponds to a distance of 100 mm to the RadarImager, as layers with a lower distance are not selectable. The distance between two selectable layers is 2.726 mm.
To calculate the distance to the RadarImager for a specific layer index, use the following formula:
layerDistance = 100mm + layerIndex * 2.726mm
Restriction based on parameter dependency
The maximum selectable layer index is limited by the measurement configuration parameter distanceZToDeepestLayerOfInterest.
The distance to the RadarImager (z-axis) corresponding to the layer index cannot exceed this parameter configuration.
| Property | Value |
|---|---|
| type | IntVector |
| Default Values | 0 |
| minInclusive | 0 |
| maxInclusive | 147 |
Slide through the layers with the layerSelection.indexedPositions parameter to find the object of interest:
The normalAbs.kind GLOBAL parameter can be used to find the object more easily.
GenDC
- If the container mode is enabled and multiple layers are to be transferred simultaneously, the desired layers should be listed separated by commas.
- The first layer starts at 0.
- Be aware of the GenDC limitations
GenDC limitations
Example
- To receive layers 0, 1 and 2, use the list:
0,1,2 - For transmitting layers 2, 5, 10 and 11 use the list:
2,5,10,11
flip.dim_1#
This parameter allows the image to be mirrored along the direction of motion (x-axis).
| Property | Value |
|---|---|
| type | Option |
| Default Flag | false |
flip.dim_2#
This parameter allows the image to be mirrored along the antenna direction (y-axis).
| Property | Value |
|---|---|
| type | Option |
| Default Flag | false |
transpose#
This parameter allows swapping the x and y dimensions of the image.
Default setting
By the default setting the movement direction (x-axis) is displayed horizontally and the antenna direction (y-axis) is displayed vertically.
| Property | Value |
|---|---|
| type | Option |
| Default Flag | false |
channelSelection.conversion#
This parameter allows selection of the type of data to be used to generate the image.
It is possible to choose between absolute values [ABS], phase information [PHASE], or a combination of both [ABS_PHASE].
With the help of the coloring parameter, it is possible to combine this information and generate a phase image
whose pixel brightness is weighted based on the absolute values.
| Property | Value |
|---|---|
| type | Enum |
| Default Value | ABS |
| elements | [ABS, PHASE, ABS_PHASE] |
channelSelection ABS (left), PHASE (middle) and ABS_PHASE (right):
Learn more about the phase information and how to use it for specific use cases in the Radar Imager Basics guide.
normalAbs#
Parameters of this node define how the captured data is normalized and scaled to generate the image. The generated data is normalized into an 8-bit integer range for efficiency and compatibility with standard image formats. Dependent on the application the scaling of the data can be adjusted to highlight specific features within the 8-bit integer dynamic range.
Note
These parameters are only relevant for images that contain ABS information, as the PHASE information is always normalized in the range of 2π.
normalAbs.kind#
This parameter determines how the image data is normalized.
LAYER: Normalizes each layer of the image data individually based on each layer's minimum and maximum values. This type of normalization is dynamic and adjusts for each measurement.GLOBAL: Normalizes all layers of the image data equally based on the minimum and maximum values of all selectable layers. This type of normalization is also dynamic but applies the same normalization across all layers. The selectable layers inlayerSelection.indexedPositionsdepend on the selecteddistanceZToDeepestLayerOfInterest.PREDEFINED: Uses fixed predefined minimum and maximum values for normalization, ensuring that the image data is always normalized in the same way for each measurement and also equally for all layers. The minimum and maximum values are configured by the parametersminPredefinedValandmaxPredefinedVal.
| Property | Value |
|---|---|
| type | Enum |
| Default Value | LAYER |
| elements | [LAYER, GLOBAL, PREDEFINED] |
Use the LAYER normalization kind to get a guaranteed visual representation of each layer.
This normalization kind is useful to get an impression of the layer and its specific features.
The GLOBAL normalization kind is useful to compare layers to identify those with particularly high reflection factors.
Depending on the application, this is very often close to the layer of interest, and can therefore be used to find it quicker.
Examples for normalAbs.kind LAYER (left) compared to GLOBAL (right) by going through the layers:
Tip
Reload the page or press F5 to make sure the GIFs run simultaneously.
The PREDEFINED normalization kind must be selected as soon as the RadarImager is used in a production environment or the image data is used for further processing.
This is very important to ensure that the image data is always normalized in the same way and that the image data is comparable for each measurement.
The LAYER and GLOBAL normalization kinds are not suitable for this purpose, as the normalization is always based on the current measurement data.
Refer to the Image Data Normalization guide for more information about the normalization of the image data.
normalAbs.minPredefinedVal#
This parameter defines the minimum value for the normalization of the image data for the PREDEFINED normalization kind.
Restriction based on parameter dependency
This parameter is only relevant if the normalization kind normalAbs.kind is set to PREDEFINED.
| Property | Value |
|---|---|
| type | Real |
| Default Value | 0 |
| unit | % |
| minInclusive | 0 |
| maxInclusive | 100 |
Adjusting the minPredefinedVal parameter allows setting the minimum value for the normalization of the image data.
This is useful to highlight specific features within the 8-bit integer dynamic range.
See example in maxPredefinedVal section.
Refer to the Image Data Normalization guide for more information about using this parameter for normalization.
normalAbs.maxPredefinedVal#
The maxPredefinedVal parameter defines the maximum value for the normalization of the image data for the PREDEFINED normalization kind.
Restriction based on parameter dependency
This parameter is only relevant if the normalization kind normalAbs.kind is set to PREDEFINED.
The selected maxPredefinedVal must be greater than minPredefinedVal
otherwise the image will not contain any information.
| Property | Value |
|---|---|
| type | Real |
| Default Value | 100 |
| unit | % |
| minInclusive | 0 |
| maxInclusive | 100 |
Adjusting the maxPredefinedVal parameter allows setting the maximum value for the normalization of the image data.
This is useful to highlight specific features within the 8-bit integer dynamic range.
Example: Adjusting the maxPredefinedVal from the default setting 100% (left) to 41% (middle)
and the minPredefinedVal from 0% (middle) to 20% (right)
increases the dynamic range of the image data displaying the scissors:
Refer to the Image Data Normalization guide for more information about using this parameter for normalization.
normalAbs.logScale#
This parameter enables logarithmic compression of the image data, using the normalAbs.dynamics
parameter to control the effective dynamic range.
Restriction based on parameter dependency
This feature is only available for data containing ABS values as configured by the channelSelection.conversion parameter.
| Property | Value |
|---|---|
| type | Option |
| Default Flag | false |
The images below show the effect of the logScale parameter on the image data
when the normalAbs.dynamics parameter is set to 20 dB.
(left disabled, right enabled)
normalAbs.dynamics#
The dynamics parameter controls the strength of logarithmic compression, determining how input values are mapped based on their magnitude.
Restriction based on parameter dependency
This parameter is only relevant if normalAbs.logScale is enabled.
| Property | Value |
|---|---|
| type | Real |
| Default Value | 20 |
| unit | dB |
| minInclusive | 0.01 |
| maxInclusive | 390 |
For a disabled normalAbs.logScale parameter a linear scaling is applied to the image data.
For the enabled normalAbs.logScale feature,
the dynamics parameter controls how compressed the image data is after applying the logarithmic transformation.
A larger dynamics value results in a more compressed output, while a smaller value expands differences between input values.
This allows for better visibility of features with a wide dynamic range, especially in cases where the data contains both very high and very low values.
Note: Smaller dynamics values may clip or suppress lower input values more aggressively, effectively reducing sensitivity to quiet or weak signals. The unit for this parameter can be interpreted as a dynamic range in dB.
Below is an example of the effect of the dynamics parameter for the values 5 dB, 10 dB, 20 dB, 30 dB, and 40 dB.
