Skip to content

Add Bad Data

Group (Subgroup)

Synthetic Building (Misc)


This Filter adds "bad" data to an Image Geometry. This Filter is intended to add "realism" (i.e., more representative of an experimental dataset) to synthetic structures that don not have any "bad" Cells. The user can choose to add "random noise" and/or "noise" along Feature boundaries. For a given type of noise, the user must then set the volume fraction of Cells to set as "bad". The volume fractions entered apply to only the set of Cells that the noise would affect. For example, if the user chose 0.2 for the volume fraction of boundary "noise", then each boundary Cell would have a 20% chance of being changed to a "bad" Cell and all other Cells would have a 0% chance of being changed. In order to compute noise over the Feature boundaries, the Filter needs the Manhattan distances for each Cell from the Feature boundaries. Note that the computed Manhattan distances are floating point values, but this Filter requires an integer array. To create the necessary integer array, use the Convert Attributer Data Type Filter to cast the Manhattan distance array to an integer array.

All Attribute Arrays that belong to the same Attribute Matrix as the selected Feature Boundary Euclidean Distances array will have noise added to them. To flag a value as "noise", this Filter will initialize a selected tuple in the Attribute Array to 0. Note that a zero value may not necessarily represent a "bad" data point in any kind of Attribute Array.

For more information on synthetic building, visit the tutorial.


Name Type Description
Add Random Noise bool Whether to add random Poisson noise to the whole volume
Volume Fraction Random Noise float Fraction of noise to add over the whole volume
Add Boundary Noise bool Whether to add noise to the boundary Cells
Volume Fraction Boundary Noise float Fraction of noise to add to the boundary Cells

Required Geometry


Required Objects

Kind Default Name Type Component Dimensions Description
Cell Attribute Array GBEuclideanDistances int32_t (1) Manhattan distances of each Cell to the closest Feature boundary

Created Objects


Example Pipelines

Please see the description file distributed with this Plugin

DREAM.3D Mailing Lists

If you need more help with a Filter, please consider asking your question on the DREAM.3D Users Google group!