LUT Transformation 3dSee full documentation

image =	lutTransform3dImg (inImg3d,lut)
image =	lutTransform3dImg (inImg3d,pILut)

Detailed Description

application of a look-up table on each 3d volume of an input image algorithm

If the image is made of one single volume (single 3d grey levels image), the algorithm applies the look-up table provided by the user to the intensities of the image. If the image is multi-sliced (made of several volumes, like a single 3d RGB image, for instance, or a sequence 3d image, etc.), a collection of look-up tables (one table per plan) is applied to the intensities of the image.

The look-up table is defined using the ipsdk::imaproc::attr::IntensityLUT data item, that is composed of the following parameters:

• Min: the minimal considered input intensity
• BinWidth: the range of input intensities associated to each table value
• LookupTable: the table itself

Considering, for instance, a single 3d grey levels input image InImg and the lookup table LUT to apply, output image OutImg pixels will equal to:

Example of Python code :

Example imports

import PyIPSDK
import PyIPSDK.IPSDKIPLGeometricTransform as gtrans
import PyIPSDK.IPSDKIPLIntensityTransform as itrans
import PyIPSDK.IPSDKIPLGlobalMeasure as glbmsr

Code Example

    # opening of input images
    inImg = PyIPSDK.loadTiffImageFile(inputImgPath)
    lut = PyIPSDK.createIntensityLUT(0, 50, [255-i*50 for i in range(256)])
    
    autoOutImg = itrans.lutTransform3dImg(inImg, lut)

Example of C++ code :

Example informations

Header file

#include <IPSDKIPL/IPSDKIPLIntensityTransform/Processor/LUTTransform3dImg/LUTTransform3dImg.h>

Code Example

        // Sample with a generated output image
        // ------------------------------------

        ImagePtr pAutoOutImg = lutTransform3dImg(pInImg, pLut);

        // Sample with a provided output image
        // -----------------------------------

        lutTransform3dImg(pInImg, pLut, pOutImg);