Commit 3f03c5a6 authored by Jordi Inglada's avatar Jordi Inglada

Cosmetique et indentation

parent 10b2ac46
......@@ -381,7 +381,7 @@ int main( int argc, char * argv [] )
// Software Guide : BeginLatex
//
// Finally, the classifier class is connected to the Markof Random Fields filter.
// Finally, the classifier class is connected to the Markov Random Fields filter.
//
// Software Guide : EndLatex
......
......@@ -407,7 +407,7 @@ int main (int argc, char* argv[])
//
// One must also specify the origin, size and spacing of the output deformation field.
//
// Software Guide : endLatex
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
......
......@@ -133,7 +133,7 @@ int main( int argc, char* argv[] )
// Software Guide : BeginLatex
//
// If your image is not in Toulouse (in region 31 to be exact), you need to
// Now we need to
// instanciate the map projection, set the {\em zone} and {\em hemisphere}
// parameters and pass this projection to the orthorectification filter.
//
......@@ -161,7 +161,7 @@ int main( int argc, char* argv[] )
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
......@@ -180,11 +180,10 @@ int main( int argc, char* argv[] )
// orthoRectifFilter->SetInput(changeInfo->GetOutput());
// Software Guide : BeginCodeSnippet
typedef otb::PerBandVectorImageFilter<VectorImageType, VectorImageType, OrthoRectifFilterType> PerBandFilterType;
PerBandFilterType::Pointer perBandFilter=PerBandFilterType::New();
perBandFilter->SetFilter(orthoRectifFilter);
// perBandFilter->SetInput(changeInfo->GetOutput());
perBandFilter->SetInput(reader->GetOutput());
// Software Guide : EndCodeSnippet
......@@ -233,7 +232,6 @@ int main( int argc, char* argv[] )
// Software Guide : BeginCodeSnippet
// writer->SetInput(orthoRectifFilter->GetOutput());
writer->SetInput(perBandFilter->GetOutput());
writer->SetTilingStreamDivisions();
......
......@@ -368,9 +368,7 @@ int main( int argc, char *argv[] )
// you find a good compromise on the time it takes to compute one evaluation
// of the Metric. Note that it is not useful to have very fast evaluations
// of the Metric if the noise in their values results in more iterations
// being required by the optimizer to converge. You must then study the
// behavior of the metric values as the iterations progress, just as
// illustrated in section~\ref{sec:MonitoringImageRegistration}.
// being required by the optimizer to converge.
//
// \index{itk::Mutual\-Information\-Image\-To\-Image\-Metric!SetNumberOfSpatialSamples()}
// \index{itk::Mutual\-Information\-Image\-To\-Image\-Metric!Trade-offs}
......
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