Commit 98a92584 authored by Daniel McInerney's avatar Daniel McInerney

DOC: further edits to module apps

parent 5806ba13
......@@ -89,7 +89,7 @@ private:
{
SetName("DimensionalityReduction");
SetDescription("Perform Dimension reduction of the input image.");
SetDocLongDescription("Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available. It is also possible to compute the inverse transform to reconstruct the image. It is also possible to optionally export the transformation matrix to a text file.");
SetDocLongDescription("Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available. It is also possible to compute the inverse transform to reconstruct the image and to optionally export the transformation matrix to a text file.");
SetDocLimitations("This application does not provide the inverse transform and the transformation matrix export for the MAF.");
SetDocAuthors("OTB-Team");
SetDocSeeAlso(
......
......@@ -126,7 +126,7 @@ private:
{
SetName("ImageDimensionalityReduction");
SetDescription("Performs dimensionality reduction of the input image "
"according to a dimensionality reduction model file.");
"based on a dimensionality reduction model file.");
// Documentation
SetDocLongDescription("This application reduces the dimension of an input"
......@@ -162,7 +162,7 @@ private:
"TrainRegression application).");
AddParameter(ParameterType_InputFilename, "imstat", "Statistics file");
SetParameterDescription("imstat", "A XML file containing mean and standard"
SetParameterDescription("imstat", "An XML file containing mean and standard"
" deviation to center and reduce samples before prediction "
"(produced by ComputeImagesStatistics application). If this file contains"
"one more bands than the sample size, the last stat of last band will be"
......
......@@ -98,7 +98,7 @@ private:
SetParameterDescription("in","The input vector data to reduce.");
AddParameter(ParameterType_InputFilename, "instat", "Statistics file");
SetParameterDescription("instat", "A XML file containing mean and standard "
SetParameterDescription("instat", "An XML file containing mean and standard "
"deviation to center and reduce samples before dimensionality reduction "
"(produced by ComputeImagesStatistics application).");
MandatoryOff("instat");
......
......@@ -94,8 +94,8 @@ private:
AddParameter(ParameterType_InputImage, "in", "Input Image");
SetParameterDescription("in", "This will take an input image to be transformed"
" image. For FFT inverse transform, it expects a complex image as two-band"
" image in which first band represent real part and second band represent"
" imaginary part.");
" image in which the first band represents the real part and second band represents"
" the imaginary part.");
AddParameter(ParameterType_OutputImage, "out", "Output Image");
SetParameterDescription("out", "This parameter holds the output file name to"
......
......@@ -66,7 +66,7 @@ private:
// Documentation
SetDocLongDescription(
"This application computes edge features on a selected channel of the input."
"It uses different filter such as gradient, Sobel and Touzi");
"It uses different filters such as gradient, Sobel and Touzi");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......@@ -102,9 +102,9 @@ private:
// Touzi Section
AddChoice("filter.touzi", "Touzi");
SetParameterDescription("filter.touzi",
"This filter is more suited for radar images. It has a spatial parameter "
"This filter is more suited to radar images. It has a spatial parameter "
"to avoid speckle noise perturbations. The larger the radius is, "
"less sensible to the speckle noise the filter is, but micro edge will be missed.");
"the less sensitive the filter is to the speckle noise, but micro edge will be missed.");
AddParameter(ParameterType_Int, "filter.touzi.xradius", "X radius of the neighborhood");
SetDefaultParameterInt("filter.touzi.xradius", 1);
AddParameter(ParameterType_Int, "filter.touzi.yradius", "Y radius of the neighborhood");
......
......@@ -148,7 +148,7 @@ private:
SetDescription("This application is the implementation of the histogram "
"equalization algorithm. It can be used to enhance contrast in an image "
"or to reduce the dynamic of the image without losing too much contrast. "
"It offers several options as a no data value, "
"It offers several options as a nodata value, "
"a contrast limitation factor, a local version of the algorithm and "
"also a mode to equalize the luminance of the image.");
......@@ -162,7 +162,7 @@ private:
"image.\n\n"
"The application proposes several options to allow a finer result:\n\n"
"* There is an option to limit contrast. We choose to limit the contrast "
"by modifying the original histogram. To do so we clip the histogram at a "
"by modifying the original histogram. To do so, we clip the histogram at a "
"given height and redistribute equally among the bins the clipped population. "
"Then we add a local version of the algorithm.\n"
"* It is possible to apply the algorithm on tiles of the image, instead "
......
......@@ -61,7 +61,7 @@ private:
SetDescription( "Apply a smoothing filter to an image" );
SetDocLongDescription( "This application applies a smoothing filter to an "
"image. Three methodes can be used: a gaussian filter , a mean filter "
"image. Three methods can be used: a gaussian filter , a mean filter "
", or an anisotropic diffusion using the Perona-Malik algorithm." );
SetDocLimitations( "None") ;
SetDocAuthors( "OTB-Team" );
......
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