image =	normalizeImg (inImg,inputRange,outputRange)
image =	normalizeImg (inImg,outputRange)

Detailed Description

normalizes the intensity of an image from an optional given input range $InOptInputRange = [inMin, inMax]$ to a given output range $InOutputRange = [outMin, outMax]$

Note: If optional input range is not provided, image minimum and maximum intensities are used.

On output image, values are given by:

$OutImg[i] = \begin{cases} outMin & \text { if } inImg[i] < inMin \\ outMax & \text { if } inImg[i] > inMax \\ (InImg[i] - inMin) * \dfrac {outMax - outMin} {inMax - inMin} + outMin & \text { otherwise} \end{cases}$

with $[inMin, inMax]$ and $[outMin, outMax]$ respectively the input and output ranges specified by the user.

Here is an example of intensity normalization applied to a 8-bits grey level image with $[outMin, outMax]=[0, 255]$ :

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(50,  200)
    
    # image normalization computation
    outImg = itrans.normalizeImg(inImg,  outputRange)

Example of C++ code :

Example informations

Header file

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

Code Example

        // Sample with a generated output image
        // ------------------------------------
        ImagePtr pAutoOutImg;
        if(pInRange.get() != 0) {
            // Sample with a generated output image
            // ------------------------------------
            pAutoOutImg = normalizeImg(pInImg, pInRange, pOutRange);
            // Sample with a provided output image
            // -----------------------------------
            // normalize input image
            itrans::normalizeImg(pInImg, pInRange, pOutRange, pOutImg);
        }
        else {
            // Sample with a generated output image
            // ------------------------------------
            pAutoOutImg = normalizeImg(pInImg, pOutRange);
            // Sample with a provided output image
            // -----------------------------------
            // create output image
            ImageGeometryPtr pOutputImageGeometry = geometry2d(outType, sizeX, sizeY);
            pOutImg = boost::make_shared<MemoryImage>();
            pOutImg->init(*pOutputImageGeometry);
            // normalize input image
            normalizeImg(pInImg, pOutRange, pOutImg);
        }