STYLE: fix various spelling errors using codespell

CMake/Description.txt

-Remote sensing processing library developped by CNES ORFEO Toolbox (OTB) is
+Remote sensing processing library developed by CNES ORFEO Toolbox (OTB) is
   distributed as an open source library of image processing algorithms. OTB is
   based on the medical image processing library ITK and offers particular
   functionalities for remote sensing image processing in general and for high
@@ -10,4 +10,4 @@ Remote sensing processing library developped by CNES ORFEO Toolbox (OTB) is
   possible.
   .
   This package provide the new version of the Monteverdi GUI application
-  developped in Qt around the OTB library.
+  developed in Qt around the OTB library.

CMake/FindGBenchmark.cmake

@@ -11,7 +11,7 @@ endif ()
 
 if (NOT GBENCHMARK_INCLUDE_DIR)
   find_path(GBENCHMARK_INCLUDE_DIR NAMES benchmark.h PATH_SUFFIXES benchmark)
-  set(GBENCHMARK_INCLUDE_DIR ${GBENCHMARK_INCLUDE_DIR}/benchmark CACHE PATH "Google.benchmark include direcory")
+  set(GBENCHMARK_INCLUDE_DIR ${GBENCHMARK_INCLUDE_DIR}/benchmark CACHE PATH "Google.benchmark include directory")
 endif ()
 
 mark_as_advanced(GBENCHMARK_INCLUDE_DIR)

CMake/FindLibSVM.cmake

@@ -9,7 +9,7 @@
 #  LIBSVM_INCLUDE_DIR - where to find svm.h
 #  LIBSVM_INCLUDE_DIRS - libsvm includes
 #  LIBSVM_LIBRARY - where to find the LibSVM library
-#  LIBSVM_LIBRARIES - aditional libraries
+#  LIBSVM_LIBRARIES - additional libraries
 #  LIBSVM_MAJOR_VERSION - major version
 #  LIBSVM_MINOR_VERSION - minor version
 #  LIBSVM_PATCH_VERSION - patch version

CMake/FindQwt.cmake

@@ -6,7 +6,7 @@
 #  QWT_INCLUDE_DIR - where to find qwt_plot.h
 #  QWT_INCLUDE_DIRS - qwt includes
 #  QWT_LIBRARY - where to find the Qwt library
-#  QWT_LIBRARIES - aditional libraries
+#  QWT_LIBRARIES - additional libraries
 #  QWT_MAJOR_VERSION - major version
 #  QWT_MINOR_VERSION - minor version
 #  QWT_PATCH_VERSION - patch version

CMake/OTBSetStandardCompilerFlags.cmake

@@ -99,7 +99,7 @@ function(check_compiler_warning_flags c_warning_flags_var cxx_warning_flags_var)
       #-wd1419 #Needed for Intel compilers with remark  #1419: external declaration in primary source file
       #-wd1572 #Needed for Intel compilers with remark  #1572: floating-point equality and inequality comparisons are unreliable
       #-wd2259 #Needed for Intel compilers with remark  #2259: non-pointer conversion from "otb::SizeValueType={unsigned long}" to "double" may lose significant bits
-      #-wd1268 #Needed for Intel compliers with warning #1268: support for exported templates is disabled
+      #-wd1268 #Needed for Intel compilers with warning #1268: support for exported templates is disabled
     else()
       set(VerboseWarningsFlag -Wall )
     endif ()
@@ -149,7 +149,7 @@ macro(check_compiler_platform_flags)
   if(MSVC)
     if (${CMAKE_VERSION} VERSION_GREATER "2.8.10.2")
       if("${CMAKE_EXE_LINKER_FLAGS}" MATCHES "/STACK:[0-9]+")
-          message(STATUS "The size of the stack is already defined, so we dont't modified it.")
+          message(STATUS "The size of the stack is already defined, so we don't modified it.")
       else()
           set(OTB_REQUIRED_LINK_FLAGS "${OTB_REQUIRED_LINK_FLAGS} /STACK:10000000")
           message(STATUS "The stack size is set to 10 Mbytes (/STACK:10000000).")

CMake/UseJava.cmake

@@ -120,7 +120,7 @@
 #
 #   Example:
 #   create_javadoc(my_example_doc
-#     PACKAGES com.exmaple.foo com.example.bar
+#     PACKAGES com.example.foo com.example.bar
 #     SOURCEPATH ${CMAKE_CURRENT_SOURCE_PATH}
 #     CLASSPATH ${CMAKE_JAVA_INCLUDE_PATH}
 #     WINDOWTITLE "My example"

Documentation/SoftwareGuide/CMakeLists.txt

@@ -66,7 +66,7 @@ IF( NOT OTB_DATA_LARGEINPUT_ROOT )
 ENDIF( NOT OTB_DATA_LARGEINPUT_ROOT )
 
 # OTB_DATA_PATHS is searched recursively.. you need not enter sub-directories
-SET(OTB_DATA_PATHS "${OTB_DATA_ROOT}/Examples::${OTB_DATA_ROOT}/Input::${OTB_DATA_LARGEINPUT_ROOT}" CACHE STRING "Where the OTB data is. Enter a double colon seperated list.")
+SET(OTB_DATA_PATHS "${OTB_DATA_ROOT}/Examples::${OTB_DATA_ROOT}/Input::${OTB_DATA_LARGEINPUT_ROOT}" CACHE STRING "Where the OTB data is. Enter a double colon separated list.")
 
 #
 # Rebuild the Software Guide figures or not ?

Documentation/SoftwareGuide/ParseCxxExamples.pl

@@ -59,7 +59,7 @@ sub ParseCxxFile {
 
 
 
-  # The following message is a warning writen on the generated .tex
+  # The following message is a warning written on the generated .tex
   # files for preventing them from being manualy edited.
   print OUTFILE "\% Please do NOT edit this file.\n";
   print OUTFILE "\% It has been automatically generated\n";

Documentation/SoftwareGuide/StripCxxExamples.pl

@@ -55,7 +55,7 @@ sub ParseCxxFile {
 
 
 
-  # The following message is a warning writen on the generated .tex
+  # The following message is a warning written on the generated .tex
   # files for preventing them from being manualy edited.
   print OUTFILE "\/\/ Please do NOT edit this file.\n";
   print OUTFILE "\/\/ It has been automatically generated\n";

Examples/BasicFilters/BandMathXImageFilterExample.cxx

@@ -139,7 +139,7 @@ int main( int argc, char* argv[])
 //  Software Guide : BeginLatex
 //
 //  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 neigborhood of size 5x5 around this pixel (and so on for each band).
+//  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.
 //
@@ -154,7 +154,7 @@ int main( int argc, char* argv[])
 
 //  Software Guide : BeginLatex
 //
-//  Note that the importance of the averaging is driven by the names of the neigborhood variables.
+//  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:
 //
 //  Software Guide : EndLatex

Examples/BasicFilters/PrintableImageFilterExample.cxx

@@ -51,7 +51,7 @@
 //
 // The band order in the image products can be also quite tricky. It could be in the wavelength order,
 // as it is the case for Quickbird (1: Blue, 2: Green, 3: Red, 4: NIR), in this case, you
-// have to be carefull to reverse the order if you want a natural display. It could also be reverse
+// have to be careful to reverse the order if you want a natural display. It could also be reverse
 // to facilitate direct viewing, as for SPOT5 (1: NIR, 2: Red, 3: Green, 4: SWIR) but in this situations
 // you have to be careful when you process the image.
 //

Examples/ChangeDetection/KullbackLeiblerProfileChDet.cxx

@@ -59,7 +59,7 @@ int main(int argc, char * argv[])
     if (argc != 9)
       {
       std::cerr <<
-      "Detection de changements par mesure de Kullback-Leibler, optimisee par un developpement de Edgeworth\n";
+      "Detection de changements par mesure de Kullback-Leibler, optimisee par un development de Edgeworth\n";
       std::cerr << argv[0] <<
       " imgAv imgAp imgResu winSizeMin winSizeMax outRedIndex outGreenIndex outBlueIndex\n";
       return 1;

Examples/Classification/KMeansImageClassificationExample.cxx

@@ -54,7 +54,7 @@ int main(int itkNotUsed(argc), char * argv[])
 // Software Guide : EndCodeSnippet
 // Software Guide : BeginLatex
 //
-// Our classifier will be genric enough to be able to process images
+// Our classifier will be generic enough to be able to process images
 // with any number of bands. We read the images as
 // \doxygen{otb}{VectorImage}s. The labeled image will be a scalar image.
 //

Examples/Classification/SOMImageClassificationExample.cxx

@@ -57,7 +57,7 @@ int main(int itkNotUsed(argc), char * argv[])
 // Software Guide : EndCodeSnippet
 // Software Guide : BeginLatex
 //
-// Our classifier will be genric enough to be able to process images
+// Our classifier will be generic enough to be able to process images
 // with any number of bands. We read the images as
 // \doxygen{otb}{VectorImage}s. The labeled image will be a scalar image.
 //

Examples/DimensionReduction/ICAExample.cxx

@@ -203,7 +203,7 @@ int main(int itkNotUsed(argc), char* argv[])
   // \itkcaption[PCA Filter (forward trasnformation)]{Result of applying the
   // \doxygen{otb}{FastICAImageFilter} to an image. From left
   // to right:
-  // original image, color composition with first three independant
+  // original image, color composition with first three independent
   // components and output of the
   // inverse mode (the input RGB image).}
   // \label{fig:FastICA_FILTER}

Examples/DisparityMap/NCCRegistrationFilterExample.cxx

@@ -120,7 +120,7 @@ int main(int argc, char** argv)
 
   // Software Guide : BeginLatex
   //
-  // Now, we need to instanciate the NCCRegistrationFilter which is going to perform the registration:
+  // Now, we need to instantiate the NCCRegistrationFilter which is going to perform the registration:
   //
   // Software Guide : EndLatex
 

Examples/DisparityMap/SimpleDisparityMapEstimationExample.cxx

@@ -110,7 +110,7 @@ int main(int argc, char* argv[])
   // Software Guide : BeginLatex
   //
   // Then we define the metric we will use to evaluate the local registration between the fixed and
-  // the moving image. In this example we choosed the \doxygen{itk}{NormalizedCorrelationImageToImageMetric}.
+  // the moving image. In this example we chose the \doxygen{itk}{NormalizedCorrelationImageToImageMetric}.
   //
   // Software Guide : EndLatex
 
@@ -122,7 +122,7 @@ int main(int argc, char* argv[])
   // Software Guide : BeginLatex
   //
   // Disparity map estimation implies evaluation of the moving image at non-grid position. Therefore, an
-  // interpolator is needed. In this example we choosed the \doxygen{itk}{WindowedSincInterpolateImageFunction}.
+  // interpolator is needed. In this example we chose the \doxygen{itk}{WindowedSincInterpolateImageFunction}.
   //
   // Software Guide : EndLatex
 
@@ -137,7 +137,7 @@ int main(int argc, char* argv[])
 
   // Software Guide : BeginLatex
   //
-  // To perform local registration, an optimizer is needed. In this example we choosed the
+  // To perform local registration, an optimizer is needed. In this example we chose the
   // \doxygen{itk}{GradientDescentOptimizer}.
   //
   // Software Guide : EndLatex
@@ -345,7 +345,7 @@ int main(int argc, char* argv[])
 
   // Software Guide : BeginLatex
   //
-  // The disparity map estimation filter is instanciated.
+  // The disparity map estimation filter is instantiated.
   //
   // Software Guide : EndLatex
 
@@ -379,7 +379,7 @@ int main(int argc, char* argv[])
   // Software Guide : BeginLatex
   //
   // The local registration process can lead to wrong deformation values and transform parameters. To Select only
-  // points in point set for which the registration process was succesful, one can set a threshold on the final metric
+  // points in point set for which the registration process was successful, one can set a threshold on the final metric
   // value : points for which the absolute final metric value is below this threshold will be discarded. This
   // threshold can be set with the \code{SetMetricThreshold()} method.
   //

Examples/FeatureExtraction/ComplexMomentsImageFunctionExample.cxx

@@ -80,7 +80,7 @@ int main(int argc, char * argv[])
 
   //  Software Guide : BeginLatex
   //
-  // Next, we plug the input image into the complex moment fucntion
+  // Next, we plug the input image into the complex moment function
   // and we set its parameters.
   //
   //  Software Guide : EndLatex

Examples/FeatureExtraction/EdgeDensityExample.cxx

@@ -97,7 +97,7 @@ int main(int itkNotUsed(argc), char* argv[])
   // We define now the type for the function which will be used by the
   // edge density filter to estimate this density. Here we choose a
   // function which counts the number of non null pixels per area. The
-  // fucntion takes as template the type of the image to be processed.
+  // function takes as template the type of the image to be processed.
   //
   // Software Guide : EndLatex
 
@@ -120,7 +120,7 @@ int main(int itkNotUsed(argc), char* argv[])
   //
   // Finally, we can define the type for the edge density filter which
   // takes as template the input and output image types, the edge
-  // detector type, and the count fucntion type..
+  // detector type, and the count function type..
   //
   // Software Guide : EndLatex
 

Examples/FeatureExtraction/ExtractRoadExample.cxx

@@ -238,7 +238,7 @@ int main(int argc, char * argv[])
   // Software Guide : BeginLatex
   //
   // Roads are not likely to have sharp turns. Therefore we set the max angle parameter,
-  // as well as the link angular threshold. The value is typicaly $\frac{\pi}{8}$.
+  // as well as the link angular threshold. The value is typically $\frac{\pi}{8}$.
   //
   // Software Guide : EndLatex