DOC: all haralick formulas in the doxygen and add link in SG and haralick app

Documentation/SoftwareGuide/Latex/FeatureExtraction.tex

@@ -11,60 +11,34 @@ etc. They can also be measures : moments, textures, etc.
 \subsection{Haralick Descriptors}
 
 This example illustrates the use of the \doxygen{otb}{ScalarImageToTexturesFilter},
-which compute the standard Haralick's textural features~\cite{Haralick1973} presented in table~\ref{tab:haralickStandardFeatures},
-where $\mu_t$ and $\sigma_t$ are the mean and standard deviation of the row
-(or column, due to symmetry) sums, $ \mu =  $ (weighted pixel average)
-$ = \sum_{i,j}i \cdot g(i, j) =\sum_{i,j}j \cdot g(i, j) $ due to matrix summetry, and
-$ \sigma =  $ (weighted pixel variance) $ = \sum_{i,j}(i - \mu)^2 \cdot g(i, j) =\sum_{i,j}(j - \mu)^2 \cdot g(i, j)  $
-due to matrix symmetry.
-
-\begin{table}
-\begin{center}
-\begin{tabular}{|c|c|}
-\hline
-& \\
-Energy & $ f_1 = \sum_{i,j}g(i, j)^2 $ \\
-& \\
-\hline
-& \\
-Entropy & $ f_2 = -\sum_{i,j}g(i, j) \log_2 g(i, j)$, or 0 if $g(i, j) = 0$ \\
-& \\
-\hline
-& \\
-Correlation & $ f_3 = \sum_{i,j}\frac{(i - \mu)(j - \mu)g(i, j)}{\sigma^2} $ \\
-& \\
-\hline
-& \\
-Difference Moment &  $f_4 = \sum_{i,j}\frac{1}{1 + (i - j)^2}g(i, j) $ \\
-& \\
-\hline
-& \\
-Inertia (a.k.a. Contrast) & $ f_5 = \sum_{i,j}(i - j)^2g(i, j) $ \\
-& \\
-\hline
-& \\
-Cluster Shade & $ f_6 = \sum_{i,j}((i - \mu) + (j - \mu))^3 g(i, j) $ \\
-& \\
-\hline
-Cluster Prominence & $ f_7 = \sum_{i,j}((i - \mu) + (j - \mu))^4 g(i, j) $ \\
-& \\
-\hline
-& \\
-Haralick's Correlation & $ f_8 = \frac{\sum_{i,j}(i, j) g(i, j) -\mu_t^2}{\sigma_t^2} $ \\
-& \\
-\hline
-\end{tabular}
-\itkcaption[Haralick features]{Haralick features~\cite{Haralick1973} available in \doxygen{otb}{ScalarImageToTexturesFilter}}
-\end{center}
-\label{tab:haralickStandardFeatures}
-\end{table}
-
-More features are available in \doxygen{otb}{ScalarImageToAdvancedTexturesFilter}.
+which computes the standard Haralick's textural features~\cite{Haralick1973}.
+
+The \doxygen{otb}{ScalarImageToTexturesFilter} class computes 8 local Haralick
+textures features. Their formulas are available in the
+\doxygen{otb}{ScalarImageToTexturesFilter} documentation (see section
+\textit{Detailed Description} in the doxygen).
+
+Note that more features are available in
+\doxygen{otb}{ScalarImageToAdvancedTexturesFilter} and in
+\doxygen{otb}{ScalarImageToHigherOrderTexturesFilter}.
+
+\doxygen{otb}{ScalarImageToHigherOrderTexturesFilter} computes 10 advanced
+texture features. Their formulas are available in the
+\doxygen{otb}{ScalarImageToAdvancedTexturesFilter} documentation (see section
+\textit{Detailed Description} in the doxygen).
+
+\doxygen{otb}{ScalarImageToHigherOrderTexturesFilter} computes 11
+other local higher order statistics textures coefficients also based on the grey
+level run-length matrix. Formulas for these coefficients are also
+available in the doxygen documentation of the filter (see section
+\textit{Detailed Description} in the doxygen).
+
 \relatedClasses
 \begin{itemize}
 \item \doxygen{otb}{ScalarImageToAdvancedTexturesFilter}
 \item \doxygen{otb}{ScalarImageToPanTexTextureFilter}
 \item \doxygen{otb}{GreyLevelCooccurrenceIndexedList}
+\item \doxygen{otb}{ScalarImageToHigherOrderTexturesFilter}
 \end{itemize}
 
 \input{TextureExample}

Modules/Feature/Textures/include/otbScalarImageToAdvancedTexturesFilter.h

@@ -24,6 +24,7 @@
 #include "otbGreyLevelCooccurrenceIndexedList.h"
 #include "itkMacro.h"
 #include "itkImageToImageFilter.h"
+
 namespace otb
 {
 /**

Modules/Feature/Textures/include/otbScalarImageToTexturesFilter.h

@@ -64,13 +64,13 @@ namespace otb
  * (or column, due to symmetry) sums.
  *
  * Above, \f$ \mu =  \f$ (weighted pixel average) \f$ = \sum_{i, j}i \cdot g(i, j) =
- * \sum_{i, j}j \cdot g(i, j) \f$ (due to matrix summetry), and
+ * \sum_{i, j}j \cdot g(i, j) \f$ (due to matrix symmetry), and
  *
  * \f$ \sigma =  \f$ (weighted pixel variance) \f$ = \sum_{i, j}(i - \mu)^2 \cdot g(i, j) =
- * \sum_{i, j}(j - \mu)^2 \cdot g(i, j)  \f$  (due to matrix summetry)
+ * \sum_{i, j}(j - \mu)^2 \cdot g(i, j)  \f$  (due to matrix symmetry)
  *
 
- * Print references:
+ * References:
  *
  * Haralick, R.M., K. Shanmugam and I. Dinstein. 1973.  Textural Features for
  * Image Classification. IEEE Transactions on Systems, Man and Cybernetics.