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AVL.SmoothImage_Mean_Mask Method
Smooths an image by averaging pixels within a small rectangular kernel.
Namespace: | AvlNet |
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Assembly: | AVL.NET.dll |
Syntax
public static void SmoothImage_Mean_Mask( AvlNet.Image inImage, AvlNet.Region inRoi, AvlNet.MeanKernel inKernel, out AvlNet.Image outImage )
Parameters
Name | Type | Range | Default | Description | |
---|---|---|---|---|---|
![]() | inImage | AvlNet.Image | Input image. | ||
![]() | inRoi | AvlNet.Region | Range of outImage pixels to be computed. Default value: atl::NIL, or null. | ||
![]() | inKernel | AvlNet.MeanKernel | Selects a predefined kernel. | ||
![]() | outImage | AvlNet.Image | Output image. |
Description
This operation is a simplified, fast in computation, version of SmoothImage_Mean, with predefined kernel and simplified ROI handling.
Kernel used in operation can be chosen by inKernel parameter:
- Box_3x3: 3 by 3 pixels, the closest equivalent is SmoothImage_Mean call with inKernel = Box, inRadiusX = 1, inRadiusY = 1, inIterationsCount = 1
- Box_5x5: 5 by 5 pixels, the closest equivalent is SmoothImage_Mean call with inKernel = Box, inRadiusX = 2, inRadiusY = 2, inIterationsCount = 1
Although above calls are described as closest equivalent their results may vary.
Examples
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SmoothImage_Mean_Mask performed on a sample image with inKernel = Box5x5.
Hardware Acceleration
This operation is optimized for SSE2 technology for pixels of types: UINT8, SINT16.
This operation supports automatic parallelization for multicore and multiprocessor systems.
Hardware acceleration settings may be manipulated with Settings class.