BandMathXImageFilterExample.cxx¶

Example usage:

./BandMathXImageFilterExample Input/qb_RoadExtract.tif Output/qb_BandMath-res1.tif Output/qb_BandMath-res2.tif Output/context.txt


Example source code (BandMathXImageFilterExample.cxx):

//  This filter is based on the mathematical parser library muParserX.
//  The built in functions and operators list is available at:
//  \url{http://articles.beltoforion.de/article.php?a=muparserx}.
//
//  In order to use this filter, at least one input image is to be
// set. An associated variable name can be specified or not by using
// the corresponding SetNthInput method. For the jth (j=1..T) input image, if
// no associated variable name has been specified, a default variable
// name is given by concatenating the prefix "im" with the
// corresponding input index plus one (for instance, im1 is related to the first input).
// If the jth input image is multidimensional, then the variable imj represents a vector whose components are related to its bands.
// In order to access the kth band, the variable observes the following pattern : imjbk.

#include "itkMacro.h"
#include <iostream>

#include "otbVectorImage.h"
#include "otbImageFileWriter.h"

// We start by including the needed header files.

#include "otbVectorImage.h"
#include "otbImageFileWriter.h"
#include "otbBandMathXImageFilter.h"

int main(int argc, char* argv[])
{

if (argc != 5)
{
std::cerr << "Usage: " << argv[0] << " inputImageFile ";
std::cerr << " outputImageFile ";
std::cerr << " outputImageFile2";
std::cerr << " context.txt" << std::endl;
return EXIT_FAILURE;
}

//  Then, we set the classical \code{typedef}s needed for reading and
//  writing the images. The \doxygen{otb}{BandMathXImageFilter} class
//  works with \doxygen{otb}{VectorImage}.

using PixelType  = double;
using ImageType  = otb::VectorImage<PixelType, 2>;
using WriterType = otb::ImageFileWriter<ImageType>;

//  We can now define the type for the filter:

using FilterType = otb::BandMathXImageFilter<ImageType>;

//  We instantiate the filter, the reader, and the writer:

WriterType::Pointer writer = WriterType::New();
FilterType::Pointer filter = FilterType::New();

//  The reader and the writer are parametrized with usual settings:

writer->SetFileName(argv[2]);

//  The aim of this example is to compute a simple high-pass filter.
//  For that purpose, we are going to perform the difference between the original signal
//  and its averaged version. The definition of the expression that follows is only suitable for a 4-band image.
//  So first, we must check this requirement:

if (reader->GetOutput()->GetNumberOfComponentsPerPixel() != 4)
itkGenericExceptionMacro(<< "Input image must have 4 bands." << std::endl);

//  Now, we can define the expression. The variable im1 represents a pixel (made of 4 components) of the input image.
//  The variable im1b1N5x5 represents a neighborhood of size 5x5 around this pixel (and so on for each band).
//  The last element we need is the operator 'mean'. By setting its inputs with four neigborhoods, we tell this operator to process the four related bands.
//  As output, it will produce a vector of four components; this is consistent with the fact that we wish to perform a difference with im1.
//
//  Thus, the expression is as follows:

filter->SetExpression("im1-mean(im1b1N5x5,im1b2N5x5,im1b3N5x5,im1b4N5x5)");

//  Note that the importance of the averaging is driven by the names of the neighborhood variables.
//  Last thing we have to do, is to set the pipeline:

writer->SetInput(filter->GetOutput());
writer->Update();

// Figure~\ref{fig:BandMathXImageFilter} shows the result of our high-pass filter.
// \begin{figure}
// \center
// \includegraphics[width=0.45\textwidth]{qb_BandMath-res1.eps}
// \itkcaption[Band Math X]{From left to right:
// Original image, high-pass filter output.}
// \label{fig:BandMathXImageFilter}
// \end{figure}

//  Now let's see a little bit more complex example.
//  The aim now is to give the central pixel a higher weight. Moreover :
//  - we wish to use smaller neighborhoods
//  - we wish to drop the 4th band
//  - we wish to add a given number to each band.
//
//  First, we instantiate new filters to later make a proper pipeline:

WriterType::Pointer writer2 = WriterType::New();
FilterType::Pointer filter2 = FilterType::New();

writer2->SetFileName(argv[3]);

//  We define a new kernel (rows are separated by semi-colons, whereas their elements are separated by commas):

filter2->SetMatrix("kernel", "{ 0.1 , 0.1 , 0.1; 0.1 , 0.2 , 0.1; 0.1 , 0.1 , 0.1 }");

//  We then define a new constant:

filter2->SetConstant("cst", 1.0);

//  We now set the expression (note the use of 'dotpr' operator, as well as the 'bands' operator which is used as a band selector):

filter2->SetExpression("bands(im1,{1,2,3})-dotpr(kernel,im1b1N3x3,im1b2N3x3,im1b3N3x3) + {cst,cst,cst}");

//  It is possible to export these definitions to a txt file (they will be reusable later thanks to the method ImportContext):

filter2->ExportContext(argv[4]);

//  And finally, we set the pipeline:

writer2->SetInput(filter2->GetOutput());
writer2->Update();

// Figure~\ref{fig:BandMathXImageFilter2} shows the result of the second filter.
// \begin{figure}
// \center