CMake/OTBApplicationMacros.cmake

@@ -117,8 +117,6 @@ macro(otb_create_application)
    list(REMOVE_DUPLICATES OTB_APPLICATIONS_NAME_LIST)
    set(OTB_APPLICATIONS_NAME_LIST ${OTB_APPLICATIONS_NAME_LIST}
        CACHE STRING "List of all applications" FORCE)
-   mark_as_advanced(OTB_APPLICATIONS_NAME_LIST)
-
 endmacro()
 
 macro(otb_test_application)

CMake/OTBModuleExternal.cmake

@@ -71,7 +71,7 @@ else()
     set(OTB_INSTALL_DATA_DIR share/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR})
   endif()
   if(NOT OTB_INSTALL_DOC_DIR)
-    set(OTB_INSTALL_DOC_DIR share/doc/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR})
+    set(OTB_INSTALL_DOC_DIR share/doc/otb)
   endif()
   if(NOT OTB_INSTALL_PACKAGE_DIR)
     set(OTB_INSTALL_PACKAGE_DIR "lib/cmake/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR}")

CMakeLists.txt

@@ -23,7 +23,8 @@ cmake_minimum_required(VERSION 3.1.0)
 foreach(p
     CMP0025 # CMake 3.0
     CMP0042 # CMake 3.0
-    CMP0058
+    CMP0058 # CMake 3.3
+    CMP0072 # CMake 3.11
     )
   if(POLICY ${p})
     cmake_policy(SET ${p} NEW)
@@ -91,6 +92,8 @@ if( CMAKE_HOST_WIN32 )
   endif()
 
 endif()
+set(OTB_APPLICATIONS_NAME_LIST "" CACHE STRING "List of all applications" FORCE)
+mark_as_advanced(OTB_APPLICATIONS_NAME_LIST)
 
 set(OTB_CMAKE_DIR ${OTB_SOURCE_DIR}/CMake)
 set(CMAKE_MODULE_PATH ${OTB_CMAKE_DIR} ${CMAKE_MODULE_PATH})
@@ -124,7 +127,7 @@ set(main_project_name ${_OTBModuleMacros_DEFAULT_LABEL})
 # OTB version number.
 set(OTB_VERSION_MAJOR "6")
 set(OTB_VERSION_MINOR "6")
-set(OTB_VERSION_PATCH "0")
+set(OTB_VERSION_PATCH "1")
 set(OTB_VERSION_STRING "${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR}.${OTB_VERSION_PATCH}")
 
 # Monteverdi version number (follows OTB)
@@ -153,31 +156,28 @@ if(NOT OTB_INSTALL_INCLUDE_DIR)
   set(OTB_INSTALL_INCLUDE_DIR include/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR})
 endif()
 if(NOT OTB_INSTALL_APP_DIR)
-  set(OTB_INSTALL_APP_DIR "lib/otb/applications")
+  set(OTB_INSTALL_APP_DIR "${OTB_INSTALL_LIBRARY_DIR}/otb/applications")
 endif()
 if(NOT OTB_INSTALL_PYTHON_DIR)
-  set(OTB_INSTALL_PYTHON_DIR "lib/otb/python")
+  set(OTB_INSTALL_PYTHON_DIR "${OTB_INSTALL_LIBRARY_DIR}/otb/python")
 endif()
 if(NOT OTB_INSTALL_PYTHON3_DIR)
-  set(OTB_INSTALL_PYTHON3_DIR "lib/otb/python3")
+  set(OTB_INSTALL_PYTHON3_DIR "${OTB_INSTALL_LIBRARY_DIR}/otb/python3")
 endif()
 if(NOT OTB_INSTALL_JAVA_DIR)
-  set(OTB_INSTALL_JAVA_DIR "lib/otb/java")
+  set(OTB_INSTALL_JAVA_DIR "${OTB_INSTALL_LIBRARY_DIR}/otb/java")
 endif()
 if(NOT OTB_INSTALL_DATA_DIR)
-  set(OTB_INSTALL_DATA_DIR share/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR})
+  set(OTB_INSTALL_DATA_DIR "share/otb")
 endif()
+
 if(NOT OTB_INSTALL_DOC_DIR)
-  set(OTB_INSTALL_DOC_DIR share/doc/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR})
+  set(OTB_INSTALL_DOC_DIR "share/doc/otb")
 endif()
 if(NOT OTB_INSTALL_PACKAGE_DIR)
   set(OTB_INSTALL_PACKAGE_DIR "${OTB_INSTALL_LIBRARY_DIR}/cmake/OTB-${OTB_VERSION_MAJOR}.${OTB_VERSION_MINOR}")
 endif()
 
-if(NOT OTB_INSTALL_DESCR_DIR)
-  set (OTB_INSTALL_DESCR_DIR "share/otb/description")
-endif()
-
 #convert path to native for reconfiguring otbcli.bat.in
 file(TO_NATIVE_PATH "${OTB_INSTALL_APP_DIR}" OTB_INSTALL_APP_DIR_NATIVE)
 
@@ -429,11 +429,13 @@ install(FILES ${OTB_FIND_PACKAGE_SCRIPTS} DESTINATION ${OTB_INSTALL_PACKAGE_DIR}
 
 # TODO : install release notes, copyright notice, ...
 # install(FILES "LICENSE" "NOTICE" "README.txt" DESTINATION ${OTB_INSTALL_DOC_DIR} COMPONENT Runtime)
-install(FILES "LICENSE" DESTINATION ${OTB_INSTALL_DOC_DIR} COMPONENT Runtime)
+install(FILES "LICENSE" DESTINATION ${OTB_INSTALL_DOC_DIR})
 
 # Configure and install VERSION file
 configure_file(VERSION VERSION @ONLY)
-install(FILES ${OTB_BINARY_DIR}/VERSION DESTINATION ${OTB_INSTALL_DOC_DIR} COMPONENT Runtime)
+install(FILES ${OTB_BINARY_DIR}/VERSION DESTINATION ${OTB_BINARY_DIR}/${OTB_INSTALL_DATA_DIR} )
+
+install(DIRECTORY ${OTB_BINARY_DIR}/${OTB_INSTALL_DATA_DIR} DESTINATION share)
 
 if(BUILD_TESTING)
   add_subdirectory(Utilities/InstallTest)

Examples/BasicFilters/BandMathFilterExample.cxx

@@ -31,7 +31,7 @@
 //  The built in functions and operators list is available at:
 //  \url{http://muparser.sourceforge.net/mup_features.html}.
 //
-//  In order to use this filter, at least one input image is to be
+//  In order to use this filter, at least one input image should be
 // set. An associated variable name can be specified or not by using
 // the corresponding SetNthInput method. For the nth input image, if
 // no associated variable name has been specified, a default variable
@@ -57,10 +57,10 @@
 
 //  Software Guide : BeginLatex
 //
-// We start by including the needed header file.
+// We start by including the required header file.
 // The aim of this example is to compute the Normalized Difference Vegetation Index (NDVI)
-// from a multispecral image and perform a threshold on this
-// indice to extract area containing a dense vegetation canopy.
+// from a multispectral image and then apply a threshold to this
+// index to extract areas containing a dense vegetation canopy.
 //
 //  Software Guide : EndLatex
 
@@ -82,8 +82,8 @@ int main( int argc, char* argv[])
 //
 //  We start by the classical \code{typedef}s needed for reading and
 //  writing the images. The \doxygen{otb}{BandMathImageFilter} class
-// works with \doxygen{otb}{Image} as input so we need to define additional
-// filters to extract each layer of the multispectral image
+//  works with \doxygen{otb}{Image} as input, so we need to define additional
+//  filters to extract each layer of the multispectral image.
 //
 //  Software Guide : EndLatex
 
@@ -130,9 +130,9 @@ int main( int argc, char* argv[])
 
 //  Software Guide : BeginLatex
 //
-//  We need now to extract now each band from the input \doxygen{otb}{VectorImage},
+//  We now need to extract each band from the input \doxygen{otb}{VectorImage},
 //  it illustrates the use of the \doxygen{otb}{VectorImageToImageList}.
-//  Each extracted layer are inputs of the \doxygen{otb}{BandMathImageFilter}:
+//  Each extracted layer is an input to the \doxygen{otb}{BandMathImageFilter}:
 //
 //  Software Guide : EndLatex
 
@@ -183,22 +183,22 @@ int main( int argc, char* argv[])
 
 //  Software Guide : BeginLatex
 //
-// The muParser library offers also the possibility to extended existing built-in functions. For example,
-// you can use the OTB expression "ndvi(b3, b4)" with the filter. The mathematical expression would be in
-// this case \textit{if($ndvi(b3, b4)>0.4$, 255, 0)}. It will return the same result.
+//  The muParser library also provides the possibility to extend existing built-in functions. For example,
+//  you can use the OTB expression "ndvi(b3, b4)" with the filter. In this instance, the mathematical expression would be 
+//  \textit{if($ndvi(b3, b4)>0.4$, 255, 0)}, which would return the same result.
 //
 //  Software Guide : EndLatex
 
 //  Software Guide : BeginLatex
 //
-// Figure~\ref{fig:BandMathImageFilter} shows the result of the threshold over the NDVI indice
-// to a Quickbird image.
+// Figure~\ref{fig:BandMathImageFilter} shows the result of the threshold applied to the NDVI index
+// of a Quickbird image.
 // \begin{figure}
 // \center
 // \includegraphics[width=0.45\textwidth]{qb_ExtractRoad_pretty.eps}
 // \includegraphics[width=0.45\textwidth]{qb_BandMath-pretty.eps}
 // \itkcaption[Band Math]{From left to right:
-// Original image, thresholded NDVI indice.}
+// Original image, thresholded NDVI index.}
 // \label{fig:BandMathImageFilter}
 // \end{figure}
 //

Examples/BasicFilters/DEMToRainbowExample.cxx

@@ -37,12 +37,12 @@
 
 // Software Guide : BeginLatex
 //
-// In some situation, it is desirable to represent a gray level image in color for easier
+// In some situation, it is desirable to represent a gray scale image in color for easier
 // interpretation. This is particularly the case if pixel values in the image are used
 // to represent some data such as elevation, deformation map,
 // interferogram. In this case, it is important to ensure that similar
 // values will get similar colors. You can notice how this requirement
-// differ from the previous case.
+// differs from the previous case.
 //
 // The following example illustrates the use of the \doxygen{otb}{DEMToImageGenerator} class
 // combined with the \doxygen{otb}{ScalarToRainbowRGBPixelFunctor}. You can refer to the
@@ -112,7 +112,7 @@ int main(int argc, char * argv[])
 
   // Software Guide : BeginLatex
   //
-  // As in the previous example the \doxygen{itk}{ScalarToRGBColormapImageFilter} is
+  // As in the previous example, the \doxygen{itk}{ScalarToRGBColormapImageFilter} is
   // the filter in charge of calling the functor we specify to do the work for
   // each pixel. Here it is the \doxygen{otb}{ScalarToRainbowRGBPixelFunctor}.
   //
@@ -189,8 +189,8 @@ int main(int argc, char * argv[])
 
   // Software Guide : BeginLatex
   //
-  // Figure~\ref{fig:RAINBOW_FILTER} shows effect of applying the filter to
-  // a gray level image.
+  // Figure~\ref{fig:RAINBOW_FILTER} shows the effect of applying the filter to
+  // a gray scale image.
   //
 // \begin{figure}
 // \center
@@ -199,7 +199,7 @@ int main(int argc, char * argv[])
 // \includegraphics[width=0.44\textwidth]{DEMToHotImageGenerator.eps}
 // \includegraphics[width=0.44\textwidth]{DEMToReliefImageGenerator.eps}
 // \itkcaption[Grayscale to color]{The gray level DEM extracted from SRTM
-// data (top-left) and the same area in color representation.}
+// data (top-left) and the same area represented in color.}
 // \label{fig:RAINBOW_FILTER}
 // \end{figure}
 //  Software Guide : EndLatex

Examples/BasicFilters/HillShadingExample.cxx

@@ -31,8 +31,8 @@
 // lighting source and generating the corresponding shadows. This principle is called
 // hill shading.
 //
-// Using a simple functor \doxygen{otb}{HillShadingFunctor} and the dem image generated
-// using the \doxygen{otb}{DEMToImageGenerator} (refer to \ref{sec:ReadDEM}) you can easily
+// Using a simple functor \doxygen{otb}{HillShadingFunctor} and the DEM image generated
+// using the \doxygen{otb}{DEMToImageGenerator} (refer to \ref{sec:ReadDEM}), you can easily
 // obtain a representation of the DEM. Better yet, using the
 // \doxygen{otb}{ScalarToRainbowRGBPixelFunctor}, combined with the
 // \doxygen{otb}{ReliefColormapFunctor} you can easily generate the classic elevation maps.
@@ -130,7 +130,7 @@ int main(int argc, char * argv[])
     }
   // Software Guide : BeginLatex
   //
-  // After generating the dem image as in the DEMToImageGenerator example, you can declare
+  // After generating the DEM image as in the DEMToImageGenerator example, you can declare
   // the hill shading mechanism. The hill shading is implemented as a functor doing some
   // operations in its neighborhood. A convenient filter called \doxygen{otb}{HillShadingFilter}
   // is defined around this mechanism.

Examples/CMakeLists.txt

@@ -20,11 +20,7 @@
 
 ##### check if standalone project ######
 if(NOT PROJECT_NAME)
-  if(WIN32)
-    cmake_minimum_required(VERSION 2.8.8 FATAL_ERROR)
-  else()
-    cmake_minimum_required(VERSION 2.8.6 FATAL_ERROR)
-  endif()
+  cmake_minimum_required(VERSION 3.1.0)
   project(OTBExamples)
 endif()
 

Examples/ChangeDetection/ChangeDetectionFrameworkExample.cxx

@@ -26,11 +26,11 @@
 // in OTB. This framework uses the generic programming approach. All
 // change detection filters are
 // \doxygen{otb}{BinaryFunctorNeighborhoodImageFilter}s, that is, they
-// are filters taking two images as input and providing one image as
-// output. The change detection computation itself is performed on a
+// are filters taking two images as input and provide one image as
+// output. The change detection computation itself is performed on 
 // the neighborhood of each pixel of the input images.
 //
-// The first step required to build a change detection filter is to
+// The first step in building a change detection filter is to
 // include the header of the parent class.
 //
 // Software Guide : EndLatex
@@ -54,7 +54,7 @@
 // something accepting the syntax \code{foo()}. This can be
 // implemented using classical C/C++ functions, but it is preferable
 // to implement it using C++ functors. These are classical C++ classes
-// which overload the \code{()} operator. This allows using them with
+// which overload the \code{()} operator. This allows to be used with
 // the same syntax as C/C++ functions.
 //
 // Since change detectors operate on neighborhoods, the functor
@@ -107,7 +107,7 @@ public:
 // the functor used to perform the change detection operation.
 //
 // Inside the class only a few \code{typedef}s and the constructors
-// and destructors have to be declared.
+// and destructors need to be declared.
 //
 // Software Guide : EndLatex
 
@@ -152,8 +152,8 @@ private:
 
 // Software Guide : BeginLatex
 //
-// Pay attention to the fact that no \code{.txx} file is needed, since
-// filtering operation is implemented in the
+// Pay particular attention to the fact that no \code{.txx} file is needed, since
+// the filtering operation is implemented in the
 // \doxygen{otb}{BinaryFunctorNeighborhoodImageFilter} class. So all
 // the algorithmics part is inside the functor.
 //
@@ -178,7 +178,7 @@ int main(int argc, char* argv[])
   // Software Guide : BeginLatex
   //
   // As usual, we start by defining the image types. The internal
-  // computations will be performed with floating point precision,
+  // computations will be performed using floating point precision,
   // while the output image will be stored using one byte per pixel.
   //
   // SoftwareGuide : EndLatex
@@ -210,7 +210,7 @@ int main(int argc, char* argv[])
 
   // Software Guide : BeginLatex
   //
-  // The next step is declaring the filter for the change detection.
+  // The next step is to declare the filter for the change detection.
   //
   // SoftwareGuide : EndLatex
 

Examples/ChangeDetection/DiffChDet.cxx

@@ -107,11 +107,11 @@ int main(int argc, char* argv[])
   //
   //  The change detector will give positive and negative values
   //  depending on the sign of the difference. We are usually
-  //  interested only in the asbolute value of the difference. For
+  //  interested only in the absolute value of the difference. For
   //  this purpose, we will use the \doxygen{itk}{AbsImageFilter}. Also, before
   //  saving the image to a file in, for instance, PNG format, we will
-  //  rescale the results of the change detection in order to use all
-  //  the output pixel type range of values.
+  //  rescale the results of the change detection in order to use the full range
+  //  of values of the output pixel type.
   //
   //  Software Guide : EndLatex
 

Examples/Classification/BayesianPluginClassifier.cxx

@@ -30,19 +30,19 @@
 // In this example, we present a system that places measurement vectors into
 // two Gaussian classes. The Figure~\ref{fig:BayesianPluginClassifier} shows
 // all the components of the classifier system and the data flow. This system
-// differs with the previous k-means clustering algorithms in several
+// differs from the previous k-means clustering algorithms in several
 // ways. The biggest difference is that this classifier uses the
 // \subdoxygen{itk}{Statistics}{GaussianMembershipFunction} as membership functions
 // instead of the \subdoxygen{itk}{Statistics}{EuclideanDistanceMetric}. Since the
-// membership function is different, the membership function requires a
+// membership function is different, it requires a
 // different set of parameters, mean vectors and covariance matrices. We
 // choose the \subdoxygen{itk}{Statistics}{MeanSampleFilter} (sample mean) and the
 // \subdoxygen{itk}{Statistics}{CovarianceSampleFilter} (sample covariance) for the
-// estimation algorithms of the two parameters. If we want more robust
-// estimation algorithm, we can replace these estimation algorithms with more
+// estimation algorithms of the two parameters. If we want a more robust
+// estimation algorithm, we can replace these estimation algorithms with additional
 // alternatives without changing other components in the classifier system.
 //
-// It is a bad idea to use the same sample for test and training
+// It is a bad idea to use the same sample for both testing and training
 // (parameter estimation) of the parameters. However, for simplicity, in
 // this example, we use a sample for test and training.
 //
@@ -69,7 +69,7 @@
 
 // Software Guide : BeginLatex
 //
-// The following two files provides us the parameter estimation algorithms.
+// The following two files provides us with the parameter estimation algorithms.
 //
 // Software Guide : EndLatex
 
@@ -95,7 +95,7 @@
 // Software Guide : BeginLatex
 //
 // We will fill the sample with random variables from two normal
-// distribution using the \subdoxygen{itk}{Statistics}{NormalVariateGenerator}.
+// distributions using the \subdoxygen{itk}{Statistics}{NormalVariateGenerator}.
 //
 // Software Guide : EndLatex
 
@@ -142,9 +142,9 @@ int main(int,  char *[])
   // The following code snippet creates a NormalVariateGenerator
   // object. Since the random variable generator returns values according to
   // the standard normal distribution (the mean is zero, and the standard
-  // deviation is one) before pushing random values into the \code{sample},
-  // we change the mean and standard deviation. We want two normal (Gaussian)
-  // distribution data. We have two for loops. Each for loop uses different
+  // deviation is one), before pushing random values into the \code{sample},
+  // we change the mean and standard deviation. We need two normally (Gaussian)
+  // distributed datasets. We have two for loops, within which each uses a different
   // mean and standard deviation. Before we fill the \code{sample} with the
   // second distribution data, we call \code{Initialize(random seed)} method,
   // to recreate the pool of random variables in the
@@ -190,7 +190,7 @@ int main(int,  char *[])
   //
   // In the following code snippet, notice that the template argument for the
   // MeanSampleFilter and CovarianceFilter is \code{ClassSampleType} (i.e.,
-  // type of Subsample) instead of SampleType (i.e., type of ListSample). This
+  // type of Subsample) instead of SampleType (i.e. type of ListSample). This
   // is because the parameter estimation algorithms are applied to the class
   // sample.
   //
@@ -238,8 +238,8 @@ int main(int,  char *[])
   //
   // After creating a SampleClassifierFilter object and a
   // MaximumRatioDecisionRule object, we plug in the
-  // \code{decisionRule} and the \code{sample} to the classifier. Then,
-  // we specify the number of classes that will be considered using
+  // \code{decisionRule} and the \code{sample} to the classifier. We  
+  // then specify the number of classes that will be considered using
   // the \code{SetNumberOfClasses()} method.
   //
   // The MaximumRatioDecisionRule requires a vector of \emph{a
@@ -254,8 +254,8 @@ int main(int,  char *[])
   //   \label{eq:bayes2}
   // \end{equation}
   //
-  // The remainder of the code snippet shows how to use user-specified class
-  // labels. The classification result will be stored in a
+  // The remainder of the code snippet demonstrates how user-specified class
+  // labels are used. The classification result will be stored in a
   // MembershipSample object, and for each measurement vector, its
   // class label will be one of the two class labels, 100 and 200
   // (\code{unsigned int}).
@@ -304,7 +304,7 @@ int main(int,  char *[])
   // Euclidean distance functions. The distance function (model) has only one
   // parameter, the mean (centroid) set by the \code{SetOrigin()} method. To
   // plug-in two distance functions, we call the
-  // \code{AddMembershipFunction()} method. Then invocation of the
+  // \code{AddMembershipFunction()} method. Finally, the invocation of the
   // \code{Update()} method will perform the classification.
   //
   // Software Guide : EndLatex

Examples/Classification/ClassificationMapRegularizationExample.cxx

@@ -23,11 +23,11 @@
 //
 // After having generated a classification map, it is possible to
 // regularize such a labeled image in order to obtain more homogeneous
-// areas, which makes the interpretation of its classes easier. For this
+// areas, which facilitates its interpretation. For this
 // purpose, the \doxygen{otb}{NeighborhoodMajorityVotingImageFilter} was
 // implemented. Like a morphological filter, this filter uses majority
 // voting in a ball shaped neighborhood in order to set each pixel of the
-// classification map to the more representative label value in its
+// classification map to the most representative label value in its
 // neighborhood.
 //
 // In this example we will illustrate its use. We start by including the
@@ -78,7 +78,7 @@ int main(int itkNotUsed(argc), char * argv[])
 // Software Guide : BeginLatex
 //
 // We can now define the type for the neighborhood majority voting filter,
-// which is templated over its input and output images types and over its
+// which is templated over its input and output images types as well as its
 // structuring element type. Choosing only the input image type in the template
 // of this filter induces that, both input and output images types are the same
 // and that the structuring element is a ball
@@ -196,9 +196,9 @@ int main(int itkNotUsed(argc), char * argv[])
 
 // Software Guide : BeginLatex
 //
-// Moreover, since the majority voting regularization may lead to not unique
-// majority labels in the neighborhood, it is important to define which behaviour
-// the filter must have in this case. For this purpose, a Boolean parameter is used
+// Furthermore, since the majority voting regularization may lead to different 
+// majority labels in the neighborhood, in this case, it would be important to define
+// the filter's behaviour. For this purpose, a Boolean parameter is used
 // in the filter to choose whether pixels with more than one majority class are set
 // to undecidedValue (true), or to their Original labels (false = default value)
 // in the output image.

Examples/Filtering/CompositeFilterExample.cxx

@@ -287,7 +287,7 @@ int main(int argc, char* argv[])
     {
     writer->Update();
     }
-  catch (itk::ExceptionObject e)
+  catch ( itk::ExceptionObject & e )
     {
     std::cerr << "Error: " << e << std::endl;
     }

Examples/Filtering/test/CMakeLists.txt

@@ -132,13 +132,13 @@ otb_add_test(NAME fiTeMathematicalMorphologyGrayscaleFiltersTest COMMAND ${OTB_T
 
 otb_add_test(NAME fiTeLaplacianRecursiveGaussianImageFilter1Test COMMAND ${OTB_TEST_DRIVER}
   --compare-n-images ${NOTOL} 2
-    ${BASELINE}/LaplacianRecursiveGaussianImageFilteroutput5.hdr
-    ${TEMP}/LaplacianRecursiveGaussianImageFilteroutput5.hdr
+    ${BASELINE}/LaplacianRecursiveGaussianImageFilteroutput5.tif
+    ${TEMP}/LaplacianRecursiveGaussianImageFilteroutput5.tif
     ${BASELINE}/LaplacianRecursiveGaussianImageFilterOutput5.png
     ${TEMP}/LaplacianRecursiveGaussianImageFilterOutput5.png
   Execute $<TARGET_FILE:LaplacianRecursiveGaussianImageFilter1>
     ${INPUTDATA}/ROISpot5.png
-    ${TEMP}/LaplacianRecursiveGaussianImageFilteroutput5.hdr
+    ${TEMP}/LaplacianRecursiveGaussianImageFilteroutput5.tif
     5
     ${TEMP}/LaplacianRecursiveGaussianImageFilterOutput5.png
 )
@@ -148,13 +148,13 @@ otb_add_test(NAME fiTeLaplacianRecursiveGaussianImageFilter1Test COMMAND ${OTB_T
 
 otb_add_test(NAME fiTeLaplacianRecursiveGaussianImageFilter2Test COMMAND ${OTB_TEST_DRIVER}
   --compare-n-images ${NOTOL} 2
-    ${BASELINE}/LaplacianRecursiveGaussianImageFilter2output5.hdr
-    ${TEMP}/LaplacianRecursiveGaussianImageFilter2output5.hdr
+    ${BASELINE}/LaplacianRecursiveGaussianImageFilter2output5.tif
+    ${TEMP}/LaplacianRecursiveGaussianImageFilter2output5.tif
     ${BASELINE}/LaplacianRecursiveGaussianImageFilter2Output5.png
     ${TEMP}/LaplacianRecursiveGaussianImageFilter2Output5.png
   Execute $<TARGET_FILE:LaplacianRecursiveGaussianImageFilter2>
     ${INPUTDATA}/ROISpot5.png
-    ${TEMP}/LaplacianRecursiveGaussianImageFilter2output5.hdr
+    ${TEMP}/LaplacianRecursiveGaussianImageFilter2output5.tif
     5
     ${TEMP}/LaplacianRecursiveGaussianImageFilter2Output5.png
 )
@@ -210,13 +210,13 @@ otb_add_test(NAME fiTeBinaryThresholdImageFilterTest COMMAND ${OTB_TEST_DRIVER}
 
 otb_add_test(NAME fiTeDerivativeImageFilterTest COMMAND ${OTB_TEST_DRIVER}
   --compare-n-images ${NOTOL} 2
-    ${BASELINE}/DerivativeImageFilterFloatOutput.hdr
-    ${TEMP}/DerivativeImageFilterFloatOutput.hdr
+    ${BASELINE}/DerivativeImageFilterFloatOutput.tif
+    ${TEMP}/DerivativeImageFilterFloatOutput.tif
     ${BASELINE}/DerivativeImageFilterOutput.png
     ${TEMP}/DerivativeImageFilterOutput.png
   Execute $<TARGET_FILE:DerivativeImageFilter>
     ${INPUTDATA}/ROISpot5.png
-    ${TEMP}/DerivativeImageFilterFloatOutput.hdr
+    ${TEMP}/DerivativeImageFilterFloatOutput.tif
     ${TEMP}/DerivativeImageFilterOutput.png
     1 0
 )

Modules/Adapters/BoostAdapters/include/otbBoostDox.h

@@ -23,7 +23,7 @@
 
 /**\defgroup boost Boost alike helpers
  * \ingroup  Thematic
- * \brief Various helpers that are likelly to end-up in boost by themselves eventually.
+ * \brief Various helpers that are likely to eventually end-up in boost by themselves.
  * \see http://www.boost.org/
  * @{
  */

Modules/Adapters/BoostAdapters/include/otbStringUtils.h

@@ -31,6 +31,7 @@
 #pragma GCC diagnostic push
 #pragma GCC diagnostic ignored "-Wshadow"
 #pragma GCC diagnostic ignored "-Wunused-parameter"
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
 #include <boost/lexical_cast.hpp>
 #include <boost/algorithm/string.hpp>
 #include <boost/algorithm/string/predicate.hpp>
@@ -69,7 +70,7 @@ Res LexicalCast(In const& in, std::string const& kind) {
  * \param[in] errmsg a msg complement used to build the error message to
 be shown if there is \c lexical_cast exception. See \c
 otb:Utils::LexicalCast().
- * \param delims  delimitter characters (space is default)
+ * \param delims  delimiter characters (space is default)
  * \throw std::bad_alloc in case of exhausted memory
  * \throw std::runtime_error in case an element from the input string
 cannot be converted into a valid \c T instance.
@@ -95,16 +96,16 @@ ConvertStringToVector(std::string const &str, T& ret, std::string const& errmsg,
 }
 
 /**\ingroup Utils
- * split a given std::string of into key value based on given delimitter
- * string. default delimitter is '='. If the string does not have a delimitter
+ * split a given std::string of into key value based on given delimiter
+ * string. The default delimiter is '='. If the string does not have a delimiter
  * the key is set to input string and value is set to defValue.
  * \param[in] str  input string
  * \param key[out] An std::string reference where key will be stored
  * \param value[out] a reference of \cT where value will be stored
- * \param defValue[in] a default value if there is no delimitter fo
+ * \param defValue[in] a default value if there is no delimiter fo
  * \param[in] errmsg a msg complement used to build the error message to
 be shown if there is \c lexical_cast exception. See \cotb:Utils::LexicalCast().
- * \param delims  delimitter characters (space is default)
+ * \param delims  delimiter characters (space is default)
  * \throw std::bad_alloc in case of exhausted memory
  * \throw std::runtime_error in case an element from the input string
 cannot be converted into a valid \c T instance.

Modules/Adapters/BoostAdapters/include/otb_boost_expint_header.h

@@ -24,6 +24,7 @@
 #if defined(__GNUC__) || defined(__clang__)
 #pragma GCC diagnostic push
 #pragma GCC diagnostic ignored "-Wunused-parameter"
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
 #include <boost/math/special_functions/expint.hpp>
 #pragma GCC diagnostic pop
 #else

Modules/Adapters/BoostAdapters/include/otb_boost_graph_header.h

@@ -26,6 +26,7 @@
 #pragma GCC diagnostic ignored "-Wshadow"
 #pragma GCC diagnostic ignored "-Wcast-align"
 #pragma GCC diagnostic ignored "-Wunused-parameter"
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
 #include <boost/graph/graph_traits.hpp>
 #include <boost/graph/adjacency_list.hpp>
 #pragma GCC diagnostic pop

Modules/Adapters/BoostAdapters/include/otb_boost_lexicalcast_header.h

+/*
+ * Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
+ *
+ * This file is part of Orfeo Toolbox
+ *
+ *     https://www.orfeo-toolbox.org/
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef otb_boost_lexicalcast_header_h
+#define otb_boost_lexicalcast_header_h
+
+#if defined(__GNUC__) || defined(__clang__)
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
+#include <boost/lexical_cast.hpp>
+#pragma GCC diagnostic pop
+#else
+#include <boost/lexical_cast.hpp>
+#endif
+
+#endif

Modules/Adapters/BoostAdapters/include/otb_boost_math_gamma_header.h

@@ -24,6 +24,7 @@
 #if defined(__GNUC__) || defined(__clang__)
 #pragma GCC diagnostic push
 #pragma GCC diagnostic ignored "-Wunused-parameter"
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
 #include <boost/math/special_functions/gamma.hpp>
 #pragma GCC diagnostic pop
 #else

Modules/Adapters/BoostAdapters/include/otb_boost_math_normal_header.h

@@ -26,6 +26,7 @@
 #pragma GCC diagnostic ignored "-Wunused-parameter"
 #pragma GCC diagnostic ignored "-Wshadow"
 #pragma GCC diagnostic ignored "-Wmissing-field-initializers"
+#pragma GCC diagnostic ignored "-Wunused-local-typedefs"
 #include <boost/math/distributions/normal.hpp>
 #pragma GCC diagnostic pop
 #else