local 2d image skewness computation More...

IPSDKIPLSTATS_API image::ImagePtr	ipsdk::imaproc::stats::skewness2dImg (const image::ImageConstPtr &pInImg, const ipUInt32 inHalfKnlSizeX, const ipUInt32 inHalfKnlSizeY)
	wrapper function for Computation of the local skewness on a rectangular neighbourhood on a 2d image More...

IPSDKIPLSTATS_API void	ipsdk::imaproc::stats::skewness2dImg (const image::ImageConstPtr &pInImg, const ipUInt32 inHalfKnlSizeX, const ipUInt32 inHalfKnlSizeY, const image::ImagePtr &pOutImg)
	wrapper function for Computation of the local skewness on a rectangular neighbourhood on a 2d image More...

Detailed Description

local 2d image skewness computation

This algorithm computes for each pixel of output image associated local skewness on a rectangular neighbourhood of input image.

Given an input image $InImg$ and rectangular kernel half sizes $N_x = InHalfKnlSizeX$ and $N_y = InHalfKnlSizeY$ , output image values are given by :

$OutImg[x, y] = \dfrac{\sum_{o_{y}=-N_y}^{N_y}{\sum_{o_{x}=N_x}^{N_x}{(InImg[x, y]-\bar{M}[x, y])^3}}}{[\sum_{o_{y}=-N_y}^{N_y}{\sum_{o_{x}=N_x}^{N_x}{(InImg[x, y]-\bar{M}[x, y])^2}}]^{\frac{3}{2}}}$

where

$\bar{M}[x, y] = \dfrac{1}{(2 N_y + 1)(2 N_x + 1)}\sum_{o_{y}=-N_y}^{N_y}{\sum_{o_{x}=N_x}^{N_x}{InImg[x, y]}}$

See also: http://en.wikipedia.org/wiki/Skewness

Here is an example of a Skewness computation applied on a 8 bits grey level image with $InHalfKnlSizeX = InHalfKnlSizeY = 2$ :

Attributes description

Attribute description for algorithm :

Name	ToolTip	Default Initializer
ipsdk::imaproc::attr::InImg	[Input] image for processing 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::OutRealImg	[Output] image for processing operation (data contained in image buffer are reals)	ipsdk::imaproc::duplicateInOut (_pOutRealImg, _pInImg, image::eImageBufferType::eIBT_Real32)

Global Rule description

Global rule description for algorithm :
ipsdk::imaproc::matchSize (_pInImg,_pOutRealImg)

Example of Python code :

Example imports

import PyIPSDK

import PyIPSDK.IPSDKIPLStats as stats

Code Example

    # opening of input image
    inImg = PyIPSDK.loadTiffImageFile(inputImgPath)
    
    # skewness 2d image computation
    outImg = stats.skewness2dImg(inImg, 3, 3)

Example of C++ code :

Example informations

Associated library

IPSDKIPLStats

Header file

#include <IPSDKIPL/IPSDKIPLStats/Processor/Skewness2dImg/Skewness2dImg.h>

Code Example

    // opening input image
    ImageGeometryPtr pInImageGeometry = geometry2d(imageBufferType, sizeX, sizeY);
    ImagePtr pInImg = loadRawImageFile(inputImgPath, *pInImageGeometry);
    // compute skewness on input image
    ImagePtr pOutImg = skewness2dImg(pInImg, inHalfKnlSizeX, inHalfKnlSizeY);

See also: Skewness2dImgLvl1; Skewness2dImgLvl2; Skewness2dImgLvl3

Function Documentation

◆ skewness2dImg() [1/2]

IPSDKIPLSTATS_API image::ImagePtr ipsdk::imaproc::stats::skewness2dImg	(	const image::ImageConstPtr &	pInImg,
		const ipUInt32	inHalfKnlSizeX,
		const ipUInt32	inHalfKnlSizeY
	)

wrapper function for Computation of the local skewness on a rectangular neighbourhood on a 2d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException on failure

◆ skewness2dImg() [2/2]

IPSDKIPLSTATS_API void ipsdk::imaproc::stats::skewness2dImg	(	const image::ImageConstPtr &	pInImg,
		const ipUInt32	inHalfKnlSizeX,
		const ipUInt32	inHalfKnlSizeY,
		const image::ImagePtr &	pOutImg
	)

wrapper function for Computation of the local skewness on a rectangular neighbourhood on a 2d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException on failure