Commit 6abb07a1 authored by Mickael Savinaud's avatar Mickael Savinaud

STYLE

parent 76747817
......@@ -394,11 +394,11 @@ private:
"to a colored image using continuous look-up table, in order to enhance image interpretation. Several "
"look-up tables can been chosen with different color ranges.\n-The optimal method computes an optimal "
"look-up table. When processing a segmentation label image (label to color), the color difference between"
" adjacent segmented regions is maximised. When processing an unknown color image (color to label), all "
" adjacent segmented regions is maximized. When processing an unknown color image (color to label), all "
"the present colors are mapped to a continuous label list.\n - The support image method uses a color support "
"image to associate an average color to each region.");
SetDocLimitations("The segmentation optimal method does not support streaming, and thus large images. The operation color to label "
"is not implemented for the methods continuous LUT and support image LUT.\n ColorMapping uisng support image is not threaded.");
"is not implemented for the methods continuous LUT and support image LUT.\n ColorMapping using support image is not threaded.");
SetDocAuthors("OTB-Team");
SetDocSeeAlso("ImageSVMClassifier");
......@@ -487,8 +487,8 @@ private:
SetParameterFloat("method.continuous.max", 255.);
// Optimal LUT
AddChoice("method.optimal","Compute an optimised look-up table");
SetParameterDescription("method.optimal","[label to color] Compute an optimal look-up table such that neighbouring labels"
AddChoice("method.optimal","Compute an optimized look-up table");
SetParameterDescription("method.optimal","[label to color] Compute an optimal look-up table such that neighboring labels"
" in a segmentation are mapped to highly contrasted colors.\n"
"[color to label] Searching all the colors present in the image to compute a continuous label list");
AddParameter(ParameterType_Int,"method.optimal.background", "Background label");
......@@ -503,13 +503,13 @@ private:
SetParameterDescription("method.image.in", "Support image filename. LUT is calculated using the mean af pixel value on the area."
" First of all image is normalized with extrema rejection");
AddParameter(ParameterType_Int, "method.image.low", "lower quantile");
SetParameterDescription("method.image.low","lower quantile for image normalisation");
SetParameterDescription("method.image.low","lower quantile for image normalization");
MandatoryOff("method.image.low");
SetParameterInt("method.image.low", 2);
SetMinimumParameterIntValue("method.image.low", 0);
SetMaximumParameterIntValue("method.image.low", 100);
AddParameter(ParameterType_Int, "method.image.up", "upper quantile");
SetParameterDescription("method.image.up","upper quantile for image normalisation");
SetParameterDescription("method.image.up","upper quantile for image normalization");
MandatoryOff("method.image.up");
SetParameterInt("method.image.up", 2);
SetMinimumParameterIntValue("method.image.up", 0);
......
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