DifferenceOfGaussians
Applies difference of Gaussians on an image, i.e. computes difference of two Gaussian smoothed images.
Applications:Emphasizes high-frequency image features such as lines or patches / dots.
Syntax
C++
C#
Python
def DifferenceOfGaussians( inImage: Image, outImage: Image, /, *, inRoi: Region | None = None, inStdDev: float = 3.0, inStdDevRatio: float = 1.6, inKernelRelativeSize: float = 3.0, inScale: float = 1.0, diagKernelShape: Profile | None = None ) -> None
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
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inImage | Image | Input image | ||
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inRoi | Region | None | None | Range of output pixels to be computed | |
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inStdDev | float | 0.0 - ![]() |
3.0 | Smoothing standard deviation for the smaller kernel |
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inStdDevRatio | float | 1.0 - ![]() |
1.6 | Defines how many times larger is the second kernel |
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inKernelRelativeSize | float | 0.0 - 3.0 | 3.0 | A multiple of the standard deviation determining the size of the kernel |
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inScale | float | 1.0 | Output image scaling factor | |
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outImage | Image | Output image | ||
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diagKernelShape | Profile | None | None | Middle row of the kernel being used |
Hardware Acceleration
This operation is optimized for SSE2 technology for pixels of types: UINT8, SINT16, REAL.
This operation is optimized for SSE41 technology for pixels of type: UINT16.
This operation is optimized for AVX2 technology for pixels of types: UINT8, SINT16, UINT16, REAL.
This operation supports automatic parallelization for multicore and multiprocessor systems.




