Remove Noise from Surface

Description

Use this Step to remove noise from the surface data based on the similarity of neighboring data points.

Workflow

The process of configuring this Step is shown below:

Configure the input. Connect the Step ports in the graphical programming workspace or select the input under Input in the parameter configuration panel.
Determine whether to use a feature region.
Set other parameters.
Select the desired output items under Output. For an expandable output item, click ▶ and configure the Min and Max values to determine the acceptable range for the item.
Run the Step and view output.

Parameters

Parameter	Description
Use Feature Region	The Step will process all of the surface data when no feature region is used. The Step will process surface data within the region when the feature region is used. At this point, the following parameters need to be set: Feature Region Mode Choose to process data in or outside the feature region. Feature Region See Feature Region for details on setting and adjusting a feature region.
Use Intensity Image	When unselected, the Step processes the depth map; otherwise, the Step processes the intensity image.
Depth Difference Threshold	Determines whether two neighboring points are similar. If the depth value difference between two neighboring points is less than or equal to the threshold, they are considered similar and grouped into the same class.
Intensity Difference Threshold	Only visible when Use Intensity image is selected. Determines whether two neighboring points are similar. If the intensity value difference between two neighboring points is less than or equal to the threshold, they are considered similar and grouped into the same class.
Neighborhood	Determines which points around a certain point are considered neighboring points. 4-neighbor: The points directly above, below, to the left, and to the right of a point are its four neighbors. 8-neighbor: A point’s horizontal and vertical neighbors (as in 4-neighbor) and its four diagonal neighbors are its eight neighbors.
Min Number of Points in a Class	After clustering, if the number of data points in a class is lower than the set minimum, all points in that class will be considered noise and removed.
Use Statistical Filter	When noise points are connected to the main data and the differences in height or intensity values are small, use the statistical filter to further remove noise. Configure the following parameters:
Standard Deviation Calculation Method	Based on actual values: Calculate the standard deviation based on actual depth or intensity values. Based on relative values: Calculate the standard deviation based on relative depth or intensity values.
Number of Neighbors	Only visible when Based on relative values is selected in “Standard Deviation Calculation Method”. Determines how many neighbors of a point are used to calculate the differences in depth or intensity values. The mean of these differences is assigned to the point, thus updating the depth or intensity values of all data points in a class as relative values.
Standard Deviation Multiplier	Determines how many standard deviations a data point is allowed to deviate from the mean. Points outside the allowable deviation range will be removed as a noise. A smaller values means more points will be considered noise and removed.

Parameter

Description

Use Feature Region

The Step will process all of the surface data when no feature region is used.

The Step will process surface data within the region when the feature region is used. At this point, the following parameters need to be set:

Feature Region Mode

Choose to process data in or outside the feature region.
Feature Region

See Feature Region for details on setting and adjusting a feature region.

Use Intensity Image

When unselected, the Step processes the depth map; otherwise, the Step processes the intensity image.

Depth Difference Threshold

Determines whether two neighboring points are similar. If the depth value difference between two neighboring points is less than or equal to the threshold, they are considered similar and grouped into the same class.

Intensity Difference Threshold

Only visible when Use Intensity image is selected.

Determines whether two neighboring points are similar. If the intensity value difference between two neighboring points is less than or equal to the threshold, they are considered similar and grouped into the same class.

Neighborhood

Determines which points around a certain point are considered neighboring points.

4-neighbor: The points directly above, below, to the left, and to the right of a point are its four neighbors.
8-neighbor: A point’s horizontal and vertical neighbors (as in 4-neighbor) and its four diagonal neighbors are its eight neighbors.

Min Number of Points in a Class

After clustering, if the number of data points in a class is lower than the set minimum, all points in that class will be considered noise and removed.

Use Statistical Filter

When noise points are connected to the main data and the differences in height or intensity values are small, use the statistical filter to further remove noise.

Configure the following parameters:

Standard Deviation Calculation Method

Based on actual values: Calculate the standard deviation based on actual depth or intensity values.
Based on relative values: Calculate the standard deviation based on relative depth or intensity values.

Number of Neighbors

Only visible when Based on relative values is selected in “Standard Deviation Calculation Method”.

Determines how many neighbors of a point are used to calculate the differences in depth or intensity values. The mean of these differences is assigned to the point, thus updating the depth or intensity values of all data points in a class as relative values.

Standard Deviation Multiplier

Determines how many standard deviations a data point is allowed to deviate from the mean. Points outside the allowable deviation range will be removed as a noise. A smaller values means more points will be considered noise and removed.

Output Description

The output of this Step is a processed surface data that can be used as input to other Steps.

Troubleshooting

For common errors, see Error Code List.
If the error code is inconsistent with the error message, please contact Technical Support for help.

CV-W4001

Error: The “Depth Threshold” value must be greater than 0. Please enter a valid value.

Solution: Make sure the parameter value is greater than 0.

CV-W4002

Error: The set “Neighborhood” is invalid. Please select a valid option from the drop-down list.

Solution: Select a valid neighborhood from the drop-down list.

CV-W4003

Error: The “Min Number of Points in a Class” value must exceed 0. Please enter a valid value.

Solution: Make sure the parameter value is greater than 0.

CV-W4004

Error: The set “Standard Deviation Calculation Method” is invalid. Please select a valid option from the drop-down list.

Solution: Select a valid deviation calculation method from the drop-down list.

CV-W4005

Error: The “Number of Neighbors” value must be greater than 0 and less than the "Min Number of Points in a Class". Please enter a valid value.

Solution: Ensure the parameter value is greater than 0 and less than the "Min Number of Points in a Class".

CV-W4006

Error: The “Standard Deviation Multiplier” value must be greater than 0. Please enter a valid value.

Solution: Make sure the parameter value is greater than 0.

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