Normalization with a sigmoidSee full documentation

image =

sigmoidNormalizeImg (inImg,alpha,beta,outputRange)

Detailed Description

normalizes the intensity of an image with a sigmoid

On output image, values are given by:

with

• the output range specified by the user
• and floating values specified by the user

Here is an example of intensity normalization applied to Lena grey level image with =20, =20 and = [3, 247]:

Example of Python code :

Example imports

import PyIPSDK
import PyIPSDK.IPSDKIPLIntensityTransform as itrans

Code Example

    # opening of input images
    inImg = PyIPSDK.loadTiffImageFile(inputImgPath)
    
    # definition of targeted image output range
    outputRange = PyIPSDK.createRange(3, 247)

    # definition of alpha and beta input parameters
    alpha = 20
    beta = 128
    
    # image normalization computation
    autoOutImg = itrans.sigmoidNormalizeImg(inImg, alpha, beta, outputRange)

Example of C++ code :

Example informations

Header file

#include <IPSDKIPL/IPSDKIPLIntensityTransform/Processor/SigmoidNormalizeImg/SigmoidNormalizeImg.h>

Code Example

    ImagePtr pInImg = loadTiffImageFile(inputImgFilePath);
    const ipsdk::ipReal64 alpha = 20.0;
    const ipsdk::ipReal64 beta = 128.0;

    ImagePtr pAutoOutImg = sigmoidNormalizeImg(pInImg, alpha, beta, attr::createRange(3, 247));