SmoothImage_Mean_Mask

Module:	FoundationLite

Smooths an image by averaging pixels within a small rectangular kernel.

This is a faster alternative to SmoothImage_Mean when the kernel is very small.

Name	Type	Description
inImage	Image	Input image
inRoi	Region *	Range of outImage pixels to be computed
inKernel	MeanKernel	Selects a predefined kernel
outImage	Image	Output image

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.

Choose kernel size by setting inKernel input.
If a larger kernel is required, switch to SmoothImage_Mean.
If you want to remove noises from an image, consider using SmoothImage_Gauss_Mask instead.

SmoothImage_Mean_Mask performed on a sample image with inKernel = Box5x5.

This operation is optimized for SSE2 technology for pixels of types: UINT8, SINT16.

This operation is optimized for AVX2 technology for pixels of types: SSE2: UINT8, SINT16.

This operation is optimized for NEON technology for pixels of types: UINT8, SINT8, UINT16, SINT16.

This operation supports automatic parallelization for multicore and multiprocessor systems.

This filter can throw an exception to report error. Read how to deal with errors in Error Handling.

List of possible exceptions:

Error type	Description
DomainError	Region exceeds an input image in SmoothImage_Mean_Mask.

This filter is available on Basic Complexity Level.

This filter is member of SmoothImage filter group.