image = maxPropagation3dImg (inImg3d)

Detailed Description

propagation of maxima in a 3d image

Maxima propagation algorithm allows to propagate maximum grayscale values inside particules separated by zero grayscale pixel values with respect to a given neighborhood 3d policy (see 3d neighborhood models).

Two versions of this algorithm are implemented which can be selected using attribute InOptOptimizationPolicy which associated to enumerate ipsdk::imaproc::attr::eProcessingOptimizationPolicy :

a 'fast' version using a binary and a label intermediate image (which can optionally be provided via OutOptWk1BinImg and OutOptWk1LabelImg attributes)
a low memory consumption iterative algorithm which propagate maxima until convergence.

An example of propagation of maxima operation is illustrated in 2d case : see Max Propagation 2d.

Example of Python code :

Example imports

import PyIPSDK

import PyIPSDK.IPSDKIPLAdvancedMorphology as advmorpho

Code Example

    # opening of input image
    inImg = PyIPSDK.loadTiffImageFile(inputImgPath)
    
    # maxima 3d propagation computation
    outImg = advmorpho.maxPropagation3dImg(inImg)

Example of C++ code :

Example informations

Header file

#include <IPSDKIPL/IPSDKIPLAdvancedMorphology/Processor/MaxPropagation3dImg/MaxPropagation3dImg.h>

Code Example

        // opening input image
        ImagePtr pInImg3d = loadTiffImageFile(inputImgPath);
        // compute maximum propagation on input image
        ImagePtr pOutImg = maxPropagation3dImg(pInImg3d);