image = l1Norm3Img (inImg1,inImg2,inImg3)

Detailed Description

Computation of L1 (taxicab) norm of three images algorithm.

This algorithm allows to compute L1 norm (taxicab norm) of three images. Given three input images $InImg1$ , $InImg2$ and $InImg3$ , output image values are defined by :

$OutImg[i] = \lvert InImg1[i] \rvert + \lvert InImg2[i] \rvert + \lvert InImg3[i] \rvert$

Here is an example of a L1 norm computation applied to three floating point grey level input images :

See also: http://en.wikipedia.org/wiki/Norm_%28mathematics%29#Euclidean_norm

Example of Python code :

Example imports

import PyIPSDK

import PyIPSDK.IPSDKIPLArithmetic as arithm

Code Example

    # opening of input images
    inImg1 = PyIPSDK.loadTiffImageFile(inputImg1Path)
    inImg2 = PyIPSDK.loadTiffImageFile(inputImg2Path)
    inImg3 = PyIPSDK.loadTiffImageFile(inputImg3Path)
    
    # computation of L1 norm of the 3 input images
    outImg = arithm.l1Norm3Img(inImg1, inImg2, inImg3)

Example of C++ code :

Example informations

Header file

#include <IPSDKIPL/IPSDKIPLArithmetic/Processor/L1Norm3Img/L1Norm3Img.h>

Code Example

    // opening input image
    ImagePtr pInImg = loadTiffImageFile(inputImgPath);
    // compute gradient on input image
    GradientXYZImg gradientXYZ = gaussianGradient3dImg(pInImg, 3.0f);
    // compute norm on previous gradients
    ImagePtr pOutImg = l1Norm3Img(gradientXYZ._pXGradImg, gradientXYZ._pYGradImg, gradientXYZ._pZGradImg);