DOC:obia

Examples/OBIA/otbRadiometricAttributesLabelMapFilterExample.cxx

@@ -26,7 +26,7 @@
 //  This example shows the basic approch to perform object based analysis on a image.
 //  The input image is firstly segmented using the \doxygen{otb}{MeanShiftImageFilter}
 //  Then each segmented region is converted to a Map of labeled objects.
-//  After the \doxygen{otb}{RadiometricAttributesLabelMapFilter}  computes computes 
+//  After the \doxygen{otb}{RadiometricAttributesLabelMapFilter}  computes 
 //  radiometric attributes for each object.
 //  Images are supposed to be standard 4-bands image (B,G,R,NIR). The
 //  index of each channel can be set via the Set***ChannelIndex()
@@ -129,11 +129,12 @@ int main(int argc, char * argv[])
   // types.
   //
   //  Software Guide : EndLatex
+// Software Guide : BeginCodeSnippet
   filter->SetInput(reader->GetOutput());	
-
+// Software Guide : EndCodeSnippet
   LabelMapFilterType::Pointer labelMapFilter = LabelMapFilterType::New();
   labelMapFilter->SetInput(filter->GetLabeledClusteredOutput());
-  labelMapFilter->SetBackgroundValue(itk::NumericTraits<LabelType>::max());
+  labelMapFilter->SetBackgroundValue(itk::NumericTraits<LabelType>::min());
   
   ShapeLabelMapFilterType::Pointer shapeLabelMapFilter = ShapeLabelMapFilterType::New();
   shapeLabelMapFilter->SetInput(labelMapFilter->GetOutput());
@@ -143,28 +144,62 @@ int main(int argc, char * argv[])
   statisticsLabelMapFilter->SetInput2(reader->GetOutput());
   
   statisticsLabelMapFilter->Update();
-
+  //  Software Guide : BeginLatex
+  //
+  // Instantiate the  \doxygen{otb}{RadiometricAttributesLabelMapFilter} to
+  // compute radiometric value on each label object.
+  //
+  //  Software Guide : EndLatex
   RadiometricLabelMapFilterType::Pointer radiometricLabelMapFilter = RadiometricLabelMapFilterType::New();
   radiometricLabelMapFilter->SetInput1(statisticsLabelMapFilter->GetOutput());
   radiometricLabelMapFilter->SetInput2(vreader->GetOutput());
  
+  //  Software Guide : BeginLatex
+  // 
+  //  Then, we specify the red and the near infrared channels 
+  // 
+  //
+  //  Software Guide : EndLatex
   radiometricLabelMapFilter->SetRedChannelIndex(2);
   radiometricLabelMapFilter->SetNIRChannelIndex(3);
   radiometricLabelMapFilter->Update();
 
+  //  Software Guide : BeginLatex
+  // 
+  //  The \doxygen{otb}{AttributesMapOpeningLabelMapFilter} will proceed the selection. 
+  // There are three parameters. \code{AttributeName} specifies the radiometric attribute, \code{Lambda} 
+  // controls the thresholding of the input and \code{ReverseOrdering} make this filter to remove the 
+  // object with an attribute value greater than \code{Lambda} instead.   
+  // 
+  //
+  //  Software Guide : EndLatex
   OpeningLabelMapFilterType::Pointer opening = OpeningLabelMapFilterType::New();
   opening->SetInput(radiometricLabelMapFilter->GetOutput());
   opening->SetAttributeName(attr);
-  opening->SetReverseOrdering(lowerThan);
   opening->SetLambda(thresh);
-
+  opening->SetReverseOrdering(lowerThan);
+  
+  //  Software Guide : BeginLatex
+  // 
+  //  Then, Label object selected are transform in a Label Image using the \doxygen{itk}{LabelMapToLabelImageFilter}  
+  // 
+  //
+  //  Software Guide : EndLatex
   LabelMapToLabeledImageFilterType::Pointer labelMap2LabeledImage = LabelMapToLabeledImageFilterType::New();
   labelMap2LabeledImage->SetInput(opening->GetOutput());
 
+  // Software Guide : BeginLatex
+  //
+  // And finally, we declare the writer and call its \code{Update()} method to
+  // trigger the full pipeline execution.
+  //
+  // Software Guide : EndLatex
+
+  // Software Guide : BeginCodeSnippet
   WriterType::Pointer writer = WriterType::New();
   writer->SetFileName(outfname);
   writer->SetInput(labelMap2LabeledImage->GetOutput());
   writer->Update();
- 
+  // Software Guide : EndCodeSnippet
   return EXIT_SUCCESS;
 }