Mean Smoothing 3d

Smooth an input 3d image computing local mean of pixels. More...

IPSDKIPLFILTERING_API image::ImagePtr	ipsdk::imaproc::filter::meanSmoothing3dImg (const image::ImageConstPtr &pInImg3d, const ipUInt32 inHalfKnlSizeX, const ipUInt32 inHalfKnlSizeY, const ipUInt32 inHalfKnlSizeZ)
	wrapper function for Mean filter used to blur a 3d image More...
IPSDKIPLFILTERING_API void	ipsdk::imaproc::filter::meanSmoothing3dImg (const image::ImageConstPtr &pInImg3d, const ipUInt32 inHalfKnlSizeX, const ipUInt32 inHalfKnlSizeY, const ipUInt32 inHalfKnlSizeZ, const image::ImagePtr &pOutImg)
	wrapper function for Mean filter used to blur a 3d image More...

Detailed Description

Smooth an input 3d image computing local mean of pixels.

This low-pass 3d filter, also none as "box blur filter" or "box linear filter", computes for each pixel the average value of its neighboring pixels.

On output image values are given by:

where :

• is defined by InHalfKnlSizeX attribute
• is defined by InHalfKnlSizeY attribute
• is defined by InHalfKnlSizeZ attribute

Input and output images must have same size.

Here is an example of a Mean smoothing operation applied to an 8-bits grey levels input image (with ) :

See also

http://en.wikipedia.org/wiki/Box_blur

Attributes description

Attribute description for algorithm :

Name	ToolTip	Default Initializer
ipsdk::imaproc::attr::InImg3d	[Input] 3d image for operation	X
ipsdk::imaproc::attr::InHalfKnlSizeX	[Input] half kernel size along X axis for operation	X
ipsdk::imaproc::attr::InHalfKnlSizeY	[Input] half kernel size along Y axis for operation	X
ipsdk::imaproc::attr::InHalfKnlSizeZ	[Input] half kernel size along Z axis for operation	X
ipsdk::imaproc::attr::OutImg	[Output] image for processing operation	ipsdk::imaproc::duplicateInOut (_pOutImg, _pInImg3d)

Global Rule description

Global rule description for algorithm :
ipsdk::imaproc::matchSize (_pInImg3d,_pOutImg)

Example of Python code :

Example imports

import PyIPSDK
import PyIPSDK.IPSDKIPLFiltering as filter

Code Example

    # opening of input images
    inImg = PyIPSDK.loadTiffImageFile(inputImgPath)
    
    # mean smoothing filter 3d computation
    outImg = filter.meanSmoothing3dImg(inImg, 3, 3, 3)

Example of C++ code :

Example informations

Associated library

IPSDKIPLFiltering

Header file

#include <IPSDKIPL/IPSDKIPLFiltering/Processor/MeanSmoothing3dImg/MeanSmoothing3dImg.h>

Code Example

    // opening input image
    ImageGeometryPtr pImageGeometry = geometry3d(imageBufferType, sizeX, sizeY, sizeZ);
    boost::shared_ptr<MemoryImage> pInImg(boost::make_shared<MemoryImage>());
    pInImg->init(*pImageGeometry);

    // we use a customized randomImg function, instead of the IPSDK randomImg algorithm that
    // can be found in IPSDKIPLUtility, because we want that the content of the generated random image
    // is always the same each time the application is executed
    randomImg(0, 0, 150, pInImg);
        
    // compute gaussian smoothing on input image
    ImagePtr pOutImg = meanSmoothing3dImg(pInImg, inHalfKnlSizeX, inHalfKnlSizeY, inHalfKnlSizeZ);

See also

MeanSmoothing3dImgLvl1

MeanSmoothing3dImgLvl2

Function Documentation

meanSmoothing3dImg() [1/2]

IPSDKIPLFILTERING_API image::ImagePtr ipsdk::imaproc::filter::meanSmoothing3dImg	(	const image::ImageConstPtr &	pInImg3d,
		const ipUInt32	inHalfKnlSizeX,
		const ipUInt32	inHalfKnlSizeY,
		const ipUInt32	inHalfKnlSizeZ
	)

wrapper function for Mean filter used to blur a 3d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException

on failure

meanSmoothing3dImg() [2/2]

IPSDKIPLFILTERING_API void ipsdk::imaproc::filter::meanSmoothing3dImg	(	const image::ImageConstPtr &	pInImg3d,
		const ipUInt32	inHalfKnlSizeX,
		const ipUInt32	inHalfKnlSizeY,
		const ipUInt32	inHalfKnlSizeZ,
		const image::ImagePtr &	pOutImg
	)

wrapper function for Mean filter used to blur a 3d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException

on failure