genre | Kernel |
authors | Olaf Konrad, Wolf Spindler |
package | MeVisLab/Standard |
dll | MLKernel |
definition | MLKernel.def |
see also | Convolution, ExtendedConvolution, KernelEditor |
keywords | edge, detect, kernel, filter, interval, gradient, ExtendedConvolution, Convolution, Roberts |
The module Sobel3D computes gradients of a grey-value image by applying a Sobel kernel for each main axis direction.
The module can also compute the gradients strengths and a gradient vector image.
autoCalcMinMax: Bool | Min. Threshold: Float | useMinMax: Bool |
Border Handling: Enum | Non Edge Value: Float | |
Edge Value: Float | outputMax: Double | |
Fill Value: Double | outputMin: Double | |
FilterMode: Enum | referenceExtentMode: Enum | |
Max: Double | Scale with voxel size: Bool | |
Max. Threshold: Float | setAutoMinMax: Trigger | |
Min: Double | Use: Bool |
Defines the border handling mode.
See Border Handling in Kernel Operations for details.
Values:
Title | Name |
---|---|
No Pad | NoPad |
Pad Src Fill | PadSrcFill |
Pad Dst Fill | PadDstFill |
Pad Dst Fill With Orig | PadDstFillWithOrig |
Pad Src Undefined | PadSrcUndefined |
Pad Dst Undefined | PadDstUndefined |
Pad Src Clamp | PadSrcClamp |
Sets the fill value for certain Border Handling modes.
Sets the minimum value threshold for outputting a subset of voxel.
Sets the maximum value threshold for outputting a subset of voxel.
If checked, the module outputs only on a subset of voxels defined by a value range.
Set the minimum value of one kernel convolution result for thresholding in Edge Detection or in Estimation mode.
Set the maximum value of one kernel convolution result for thresholding in Edge Detection or in Estimation mode.
If in Edge Detection mode, this value will be set into the output image when the convolution value lies within the threshold range.
If in Edge Detection mode, this value will be set into the output image when the convolution value lies outside of the threshold value.
If checked and in Gradient Strength mode, each resulting convolution value is divided by the voxel size in the particular (xyz) direction.
Sets the filter mode of this module.
Values:
Title | Name | Description |
---|---|---|
Gradient Strength | Gradient Strength | The resulting sum of the kernel convolutions is written into the ouput image, which is a grey-value image representing the strengths of the gradients in each voxel. |
Edge Detection | Edge Detection | Thresholds the convolution values in each direction: if any of these values is within the threshold range, an Edge Value is written into the output image, a Non Edge Value is written else, resulting in a binary edge image. |
Estimation | Estimation | The values of the three convolutions are used as vector components, where the x,y,z values are coded into r,g,b values of the output image, resulting in a RGB-image. |