Commit b0e27774 authored by Cédric Traizet's avatar Cédric Traizet

Merge branch 'develop' into regression_refactoring

parents 2fabfa17 cb2f6d1b
......@@ -5,7 +5,6 @@
<name>TestApplication</name>
<descr>This application helps developers to test parameters types</descr>
<doc>
<name>Test</name>
<longdescr>The purpose of this application is to test parameters types.</longdescr>
<authors>OTB-Team</authors>
<limitations>None</limitations>
......
......@@ -152,3 +152,15 @@ following repositories with these command-lines:
http://download.opensuse.org/repositories/home:/tzotsos/openSUSE_Tumbleweed/ tzotsos
and then add the OTB packages as shown above.
Archlinux
~~~~~~~~~~
Package is in AUR (Arch User Repository).
You will then need to run (if you use yaourt, you could use trizen instead):
::
yaourt -S orfeo-toolbox
......@@ -68,7 +68,6 @@ private:
// \begin{description}
// \item[\code{SetName()}] Name of the application.
// \item[\code{SetDescription()}] Set the short description of the class.
// \item[\code{SetDocName()}] Set long name of the application (that can be displayed \dots).
// \item[\code{SetDocLongDescription()}] This methods is used to describe the class.
// \item[\code{SetDocLimitations()}] Set known limitations (threading, invalid pixel type \dots) or bugs.
// \item[\code{SetDocAuthors()}] Set the application Authors. Author List. Format : "John Doe, Winnie the Pooh" \dots
......@@ -81,7 +80,6 @@ private:
"Pay attention, it includes Latex snippets in order to generate "
"software guide documentation");
SetDocName("Example");
SetDocLongDescription(
"The purpose of this application is "
"to present parameters types,"
......
......@@ -49,7 +49,6 @@ private:
SetDescription("Change detection by Multivariate Alteration Detector (MAD) algorithm");
// Documentation
SetDocName("Multivariate Alteration Detector");
SetDocLongDescription("This application performs change detection between two multispectral"
" images using the Multivariate Alteration Detector (MAD) [1]"
" algorithm.\n\n"
......
......@@ -62,7 +62,6 @@ private:
SetName("ClassificationMapRegularization");
SetDescription("Filters the input labeled image using Majority Voting in a ball shaped neighbordhood");
SetDocName("Classification Map Regularization");
SetDocLongDescription(
"This application filters the input labeled image (with a maximal class label = 65535) using Majority Voting in a ball shaped neighbordhood."
......
......@@ -109,7 +109,6 @@ private:
SetDescription("Computes the confusion matrix of a classification");
// Documentation
SetDocName("Confusion matrix Computation");
SetDocLongDescription("This application computes the confusion matrix of a classification map relative to a ground truth dataset. "
"This ground truth can be given as a raster or a vector data. Only reference and produced pixels with values different "
"from NoData are handled in the calculation of the confusion matrix. The confusion matrix is organized the following way: "
......
......@@ -48,7 +48,6 @@ private:
void DoInit() override
{
SetName("ComputeImagesStatistics");
SetDocName("Compute Images second order statistics");
SetDescription("Computes global mean and standard deviation for each band "
"from a set of images and optionally saves the results in an XML file.");
SetDocLongDescription("This application computes a global mean and standard deviation "
......
......@@ -51,7 +51,6 @@ private:
SetName("ComputeOGRLayersFeaturesStatistics");
SetDescription("Compute statistics of the features in a set of OGR Layers");
SetDocName("ComputeOGRLayersFeaturesStatistics");
SetDocLongDescription("Compute statistics (mean and standard deviation) of the features in a set of OGR Layers, and write them in an XML file. This XML file can then be used by the training application.");
SetDocLimitations("Experimental. For now only shapefiles are supported.");
SetDocAuthors("David Youssefi during internship at CNES");
......
......@@ -97,7 +97,6 @@ private:
{
SetName("FusionOfClassifications");
SetDescription("Fuses several classifications maps of the same image on the basis of class labels.");
SetDocName("Fusion of Classifications");
SetDocLongDescription("This application allows you to fuse several classification maps and produces a single more robust classification map. "
"Fusion is done either by mean of Majority Voting, or with the Dempster Shafer combination method on class labels.\n\n"
" - MAJORITY VOTING: for each pixel, the class with the highest number of votes is selected.\n"
......
......@@ -80,7 +80,6 @@ private:
SetDescription("Performs a classification of the input image according to a model file.");
// Documentation
SetDocName("Image Classification");
SetDocLongDescription("This application performs an image classification based on a model file produced by the TrainImagesClassifier application. Pixels of the output image will contain the class labels decided by the classifier (maximal class label = 65535). The input pixels can be optionally centered and reduced according to the statistics file produced by the ComputeImagesStatistics application. An optional input mask can be provided, in which case only input image pixels whose corresponding mask value is greater than 0 will be classified. By default, the remaining of pixels will be given the label 0 in the output image.");
SetDocLimitations("The input image must have the same type, order and number of bands than the images used to produce the statistics file and the SVM model file. If a statistics file was used during training by the TrainImagesClassifier, it is mandatory to use the same statistics file for classification. If an input mask is used, its size must match the input image size.");
......
......@@ -371,7 +371,6 @@ private:
SetName("KMeansClassification");
SetDescription("Unsupervised KMeans image classification");
SetDocName("Unsupervised KMeans image classification");
SetDocLongDescription("Unsupervised KMeans image classification. "
"This is a composite application, using existing training and classification applications. "
"The SharkKMeans model is used.\n\n"
......
......@@ -63,7 +63,6 @@ private:
SetDescription("Compute sampling rate for an input set of images.");
// Documentation
SetDocName("Multi-image sampling rate estimation");
SetDocLongDescription("The application computes sampling rates for a set of"
" input images. Before calling this application, each pair of image and "
"training vectors has to be analysed with the application "
......
......@@ -60,7 +60,6 @@ private:
SetName("OGRLayerClassifier");
SetDescription("Classify an OGR layer based on a machine learning model and a list of features to consider.");
SetDocName("OGRLayerClassifier");
SetDocLongDescription("This application will apply a trained machine learning model on the selected feature to get a classification of each geometry contained in an OGR layer. The list of feature must match the list used for training. The predicted label is written in the user defined field for each geometry.");
SetDocLimitations("Experimental. Only shapefiles are supported for now.");
SetDocAuthors("David Youssefi during internship at CNES");
......
......@@ -72,7 +72,6 @@ private:
SetDescription("Computes statistics on a training polygon set.");
// Documentation
SetDocName("Polygon Class Statistics");
SetDocLongDescription("Process a set of geometries intended for training (they should have a field giving the associated "
"class). The geometries are analyzed against a support image to compute statistics:\n\n"
"* Number of samples per class\n"
......
......@@ -119,7 +119,6 @@ private:
SetDescription("Performs a prediction of the input image according to a regression model file.");
// Documentation
SetDocName("Predict Regression");
SetDocLongDescription("This application predict output values from an input"
" image, based on a regression model file produced by"
" the TrainRegression application. Pixels of the "
......
......@@ -82,7 +82,6 @@ private:
SetDescription("SOM image classification.");
// Documentation
SetDocName("SOM Classification");
SetDocLongDescription("Unsupervised Self Organizing Map image classification.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -57,7 +57,6 @@ private:
SetDescription("Generates synthetic samples from a sample data file.");
// Documentation
SetDocName("Sample Augmentation");
SetDocLongDescription("The application takes a sample data file as "
"generated by the SampleExtraction application and "
"generates synthetic samples to increase the number of "
......
......@@ -59,7 +59,6 @@ private:
SetDescription("Extracts samples values from an image.");
// Documentation
SetDocName("Sample Extraction");
SetDocLongDescription("The application extracts samples values from an"
"image using positions contained in a vector data file. ");
SetDocLimitations("None");
......
......@@ -86,7 +86,6 @@ private:
SetDescription("Selects samples from a training vector data set.");
// Documentation
SetDocName("Sample Selection");
SetDocLongDescription(
"The application selects a set of samples from geometries "
"intended for training (they should have a field giving the associated "
......
......@@ -41,7 +41,6 @@ public:
SetDescription( "Train a classifier from multiple pairs of images and training vector data." );
// Documentation
SetDocName( "Train a classifier from multiple images" );
SetDocLongDescription(
"Train a classifier from multiple pairs of images and training vector data. "
"Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by "
......
......@@ -105,7 +105,6 @@ void DoInit() override
"Train a classifier from multiple images to perform regression.");
// Documentation
SetDocName("Train a regression model");
SetDocLongDescription(
"This application trains a classifier from multiple input images or a csv "
"file, in order to perform regression. Predictors are composed of pixel "
......
......@@ -60,7 +60,6 @@ protected:
SetDescription( "Train a classifier based on labeled geometries and a "
"list of features to consider." );
SetDocName( "Train Vector Classifier" );
SetDocLongDescription( "This application trains a classifier based on "
"labeled geometries and a list of features to consider for "
"classification.\nThis application is based on LibSVM, OpenCV Machine "
......
......@@ -91,7 +91,6 @@ private:
SetName("VectorClassifier");
SetDescription("Performs a classification of the input vector data according to a model file.");
SetDocName("Vector Classification");
SetDocAuthors("OTB-Team");
SetDocLongDescription("This application performs a vector data classification "
"based on a model file produced by the TrainVectorClassifier application."
......
......@@ -148,7 +148,6 @@ public:
SetDescription("This application computes zonal statistics");
// Documentation
SetDocName("ZonalStatistics");
SetDocLongDescription("This application computes zonal statistics from label image, or vector data. "
"The application inputs one input multiband image, and another input for zones definition. "
"Zones can be defined with a label image (inzone.labelimage.in) or a vector data layer "
......
......@@ -83,7 +83,6 @@ private:
void DoInit() override
{
SetName("HomologousPointsExtraction");
SetDocName("Homologous points extraction");
SetDescription("Compute homologous points between images using keypoints");
SetDocLongDescription("This application allows computing homologous points between images using keypoints. "
" SIFT or SURF keypoints can be used and the band on which keypoints are computed can be set independently for both images."
......@@ -101,7 +100,6 @@ private:
" The vector file is always reprojected to EPSG:4326 to allow display in a GIS."
" This is done via reprojection or by applying the image sensor models.");
// Documentation
SetDocName("Homologous Points Extraction");
SetDocLimitations("Full mode does not handle large images.");
SetDocSeeAlso("RefineSensorModel");
SetDocAuthors("OTB-Team");
......
......@@ -89,7 +89,6 @@ private:
{
SetName("DimensionalityReduction");
SetDescription("Perform Dimension reduction of the input image.");
SetDocName("Dimensionality reduction");
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.");
SetDocLimitations("This application does not provide the inverse transform and the transformation matrix export for the MAF.");
SetDocAuthors("OTB-Team");
......
......@@ -129,7 +129,6 @@ private:
"according to a dimensionality reduction model file.");
// Documentation
SetDocName("Image Dimensionality Reduction");
SetDocLongDescription("This application reduces the dimension of an input"
" image, based on a machine learning model file produced by"
" the TrainDimensionalityReduction application. Pixels of the "
......
......@@ -73,7 +73,6 @@ private:
SetName("TrainDimensionalityReduction");
SetDescription("Train a dimensionality reduction model");
SetDocName("Train Dimensionality Reduction");
SetDocLongDescription("Trainer for dimensionality reduction algorithms "
"(autoencoders, PCA, SOM). All input samples are used to compute the "
"model, like other machine learning models.\n"
......
......@@ -86,7 +86,6 @@ private:
SetName("VectorDimensionalityReduction");
SetDescription("Performs dimensionality reduction of the input vector data "
"according to a model file.");
SetDocName("Vector Dimensionality Reduction");
SetDocAuthors("OTB-Team");
SetDocLongDescription("This application performs a vector data "
"dimensionality reduction based on a model file produced by the "
......
......@@ -84,7 +84,6 @@ private:
SetDescription("Domain Transform application for wavelet and fourier");
// Documentation
SetDocName("DomainTransform");
SetDocLongDescription("Domain Transform application for wavelet and fourier.");
SetDocLimitations("This application is not streamed, check your system resources when processing large images");
SetDocAuthors("OTB-Team");
......
......@@ -64,7 +64,6 @@ private:
"selected channel");
// Documentation
SetDocName("Edge Feature Extraction");
SetDocLongDescription(
"This application computes edge features on a selected channel of the input."
"It uses different filter such as gradient, Sobel and Touzi");
......
......@@ -59,7 +59,6 @@ private:
SetDescription("Detect line segments in raster");
// Documentation
SetDocName("Line segment detection");
SetDocLongDescription(
"This application detects locally straight contours in a image."
" It is based on Burns, Hanson, and Riseman method and use an a contrario "
......
......@@ -153,7 +153,6 @@ private:
"also a mode to equalize the luminance of the image.");
// Documentation
SetDocName("Contrast Enhancement");
SetDocLongDescription("This application is the implementation of the "
"histogram equalization algorithm. The idea of the algorithm is to use "
"the whole available dynamic. In order to do so it computes a histogram "
......
......@@ -60,7 +60,6 @@ private:
SetName( "Smoothing" );
SetDescription( "Apply a smoothing filter to an image" );
SetDocName( "Smoothing" );
SetDocLongDescription( "This application applies a smoothing filter to an "
"image. Three methodes can be used: a gaussian filter , a mean filter "
", or an anisotropic diffusion using the Perona-Malik algorithm." );
......
......@@ -48,7 +48,6 @@ private:
SetDescription("Perform P+XS pansharpening");
// Documentation
SetDocName("Bundle to perfect sensor");
SetDocLongDescription("This application performs P+XS pansharpening. The default mode use Pan and XS sensor models to estimate the transformation to superimpose XS over Pan before the fusion (\"default mode\"). The application provides also a PHR mode for Pleiades images which does not use sensor models as Pan and XS products are already coregistered but only estimate an affine transformation to superimpose XS over the Pan.Note that this option is automatically activated in case Pleiades images are detected as input.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -77,7 +77,6 @@ private:
SetDescription("Perform P+XS pansharpening");
// Documentation
SetDocName("Pansharpening");
SetDocLongDescription("This application performs P+XS pansharpening. Pansharpening is a process of merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image. Algorithms available in the applications are: RCS, bayesian fusion and Local Mean and Variance Matching(LMVM).");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -55,7 +55,6 @@ private:
SetDescription("Estimate the number of endmembers in a hyperspectral image");
// Documentation
SetDocName("Endmember Number Estimation");
SetDocLongDescription("Estimate the number of endmembers "
"in a hyperspectral image. First, compute statistics on the image and then "
"apply an endmember number estimation algorithm using these statistics. Two "
......
......@@ -94,7 +94,6 @@ private:
SetDescription("Estimate abundance maps from an hyperspectral image and a set of endmembers.");
// Documentation
SetDocName("Hyperspectral data unmixing");
SetDocLongDescription("The application applies a linear unmixing algorithm "
"to an hyperspectral data cube. This method supposes that the mixture between "
"aterials in the scene is macroscopic and simulates a linear mixing model of "
......
......@@ -54,7 +54,6 @@ private:
SetDescription("Performs local Rx score computation on an hyperspectral image.");
// Documentation
SetDocName("Local Rx Detection");
SetDocLongDescription("Performs local Rx score computation on an input "
"hyperspectral image. For each hyperspectral pixel, the Rx score is "
"computed using statistics computed on a dual neighborhood. The dual "
......
......@@ -55,7 +55,6 @@ private:
"Component Analysis algorithm.");
// Documentation
SetDocName("Vertex Component Analysis");
SetDocLongDescription("Apply the Vertex Component Analysis [1] to "
"an hyperspectral image to extract endmembers. Given a set of mixed "
"spectral vectors (multispectral or hyperspectral), the application "
......
......@@ -240,7 +240,6 @@ private:
SetName("ColorMapping");
SetDescription("Map a label image to 8-bits RGB using look-up tables.");
SetDocName("Color Mapping");
SetDocLongDescription(
"Map a label image to a 8-bits RGB image (both ways) using different methods:\n\n"
......
......@@ -55,7 +55,6 @@ private:
SetDescription("Estimator between 2 images.");
// Documentation
SetDocName("Images comparison");
SetDocLongDescription(
"Compute MSE (Mean Squared Error), MAE (Mean Absolute Error) and PSNR (Peak Signal to Noise Ratio) between two image bands (reference and measurement). "
"The user has to set the used channel and can specify a ROI."
......
......@@ -60,7 +60,6 @@ private:
SetDescription("Concatenate a list of images of the same size into a single multi-channel image.");
// Documentation
SetDocName("Images Concatenation");
SetDocLongDescription("Concatenate a list of images of the same size into a single multi-channel image. "
"It reads the input image list (single or multi-channel) "
"and generates a single multi-channel image. The channel order is the same as the list.");
......
......@@ -196,7 +196,6 @@ private:
SetDescription("Download or list SRTM tiles");
// Documentation
SetDocName("Download or list SRTM tiles related to a set of images");
SetDocLongDescription("This application allows selecting the appropriate SRTM tiles that covers a list of images. It builds a list of the required tiles. Two modes are available: the first one download those tiles from the USGS SRTM3 website (http://dds.cr.usgs.gov/srtm/version2_1/SRTM3/), the second one list those tiles in a local directory. In both cases, you need to indicate the directory in which directory tiles will be download or the location of local SRTM files.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -73,7 +73,6 @@ private:
SetName("DynamicConvert");
SetDescription("Change the pixel type and rescale the image's dynamic");
SetDocName("Dynamic Conversion");
SetDocLongDescription(
"This application performs an image pixel type "
"conversion (short, ushort, uchar, int, uint, float and double types are "
......
......@@ -75,7 +75,6 @@ private:
SetDescription("Extract a ROI defined by the user.");
// Documentation
SetDocName("Extract ROI");
SetDocLongDescription("This application extracts a Region Of Interest with "
"user parameters. There are four mode of extraction. The standard mode "
"allows the user to enter one point (upper left corner of the region to "
......
......@@ -63,7 +63,6 @@ private:
SetName("ManageNoData");
SetDescription("Manage No-Data");
// Documentation
SetDocName("No Data management");
SetDocLongDescription("This application has two modes. The first allows building a mask of no-data pixels from the no-data flags read from the image file. The second allows updating the change the no-data value of an image (pixels value and metadata). This last mode also allows replacing NaN in images with a proper no-data value. To do so, one should activate the NaN is no-data option.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -64,7 +64,6 @@ private:
SetDescription("Build a multi-resolution pyramid of the image.");
// Documentation
SetDocName("Multi Resolution Pyramid");
SetDocLongDescription("This application builds a multi-resolution pyramid of the input image. User can specified the number of levels of the pyramid and the subsampling factor. To speed up the process, you can use the fast scheme option");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -54,7 +54,6 @@ private:
SetDescription("Get the value of a pixel.");
// Documentation
SetDocName("Pixel Value");
SetDocLongDescription("This application gives the value of a selected "
"pixel. There are three ways to designate a pixel, with its index, "
"its physical coordinate (in the physical space attached to the image), "
......
......@@ -57,7 +57,6 @@ private:
{
SetName("Quicklook");
SetDescription("Generates a subsampled version of an image extract");
SetDocName("Quick Look");
SetDocLongDescription("Generates a subsampled version of an extract of an image defined by ROIStart and ROISize.\n"
"This extract is subsampled using the ratio OR the output image Size.");
SetDocLimitations("This application does not provide yet the optimal way to decode coarser level of resolution from JPEG2000 images (like in Monteverdi).\n"
......
......@@ -54,7 +54,6 @@ private:
SetDescription("Get information about the image");
// Documentation
SetDocName("Read image information");
SetDocLongDescription("Display information about the input image like: image size, origin, spacing, metadata, projections...");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -54,7 +54,6 @@ private:
SetName("Rescale");
SetDescription("Rescale the image between two given values.");
SetDocName("Rescale Image");
SetDocLongDescription("This application scales the given image pixel intensity between two given values.\n"
"By default min (resp. max) value is set to 0 (resp. 255).\n"
"Input minimum and maximum values is automatically computed for all image bands.");
......
......@@ -54,7 +54,6 @@ private:
SetName("SplitImage");
SetDescription("Split a N multiband image into N images.");
SetDocName("Split Image");
SetDocLongDescription("This application splits a N-bands image into N mono-band images. "
"The output images filename will be generated from the output parameter. "
"Thus, if the input image has 2 channels, and the user has set as output parameter, outimage.tif, "
......
......@@ -51,7 +51,6 @@ private:
SetDescription("Fusion of an image made of several tile files.");
// Documentation
SetDocName("Image Tile Fusion");
SetDocLongDescription("Automatically mosaic a set of non overlapping tile files into a single image. Images must have a matching number of bands and they must be listed in lexicographic order.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -73,7 +73,6 @@ private:
SetDescription("Compute radiometric indices.");
// Documentation
SetDocName("Radiometric Indices");
SetDocLongDescription("This application computes radiometric indices using the relevant channels of the input image. The output is a multi band image into which each channel is one of the selected indices.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -50,7 +50,6 @@ private:
SetName("KmzExport");
SetDescription("Export the input image in a KMZ product.");
// Documentation
SetDocName("Image to KMZ Export");
SetDocLongDescription("This application exports the input image in a kmz product that can be display in the Google Earth software. The user can set the size of the product size, a logo and a legend to the product. Furthemore, to obtain a product that fits the relief, a DEM can be used.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -62,7 +62,6 @@ private:
"on several multi-band images."
);
SetDocName( "Band Math" );
SetDocLongDescription(
"This application performs a mathematical operation on several multi-band "
......
......@@ -61,7 +61,6 @@ private:
SetDescription("This application performs mathematical operations on several multiband images.");
SetDocName( "Band Math X" );
SetDocLongDescription(
"This application performs a mathematical operation on several multi-band "
......
......@@ -59,7 +59,6 @@ SetName("LocalStatisticExtraction");
SetDescription("Computes local statistical moments on every pixel in the selected channel of the input image");
// Documentation
SetDocName("Local Statistic Extraction");
SetDocLongDescription("This application computes the 4 local statistical moments on every pixel in the selected channel of the input image, over a specified neighborhood. The output image is multi band with one statistical moment (feature) per band. Thus, the 4 output features are the Mean, the Variance, the Skewness and the Kurtosis. They are provided in this exact order in the output image.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -78,7 +78,6 @@ SetName( "BinaryMorphologicalOperation" );
SetDescription( "Performs morphological operations on an input image channel" );
// Documentation
SetDocName( "Binary Morphological Operation" );
SetDocLongDescription( "This application performs binary morphological "
"operations on a mono band image or a channel of the input." );
SetDocLimitations( "None" );
......
......@@ -77,7 +77,6 @@ SetName("GrayScaleMorphologicalOperation");
SetDescription("Performs morphological operations on a grayscale input image");
// Documentation
SetDocName("Grayscale Morphological Operation");
SetDocLongDescription("This application performs grayscale morphological operations on a mono band image");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -77,7 +77,6 @@ private:
"classification on an input image channel" );
// Documentation
SetDocName( "Morphological Classification" );
SetDocLongDescription(
"This algorithm is based on the following publication:\n"
"Martino Pesaresi and Jon Alti Benediktsson, Member, IEEE: A new approach "
......
......@@ -71,7 +71,6 @@ private:
SetDescription( "Perform a geodesic morphology based image analysis on an input image channel" );
// Documentation
SetDocName( "Morphological Multi Scale Decomposition" );
SetDocLongDescription(
"This application recursively apply geodesic decomposition. \n"
"\n"
......
......@@ -77,7 +77,6 @@ private:
SetDescription( "Performs morphological profiles analysis on an input image channel." );
// Documentation
SetDocName( "Morphological Profiles Analysis" );
SetDocLongDescription( "This algorithm is derived from the following publication:\n\n"
"Martino Pesaresi and Jon Alti Benediktsson, Member, IEEE: A new approach\n"
......
......@@ -130,7 +130,6 @@ private:
SetName("OpticalCalibration");
SetDescription("Perform optical calibration TOA/TOC (Top Of Atmosphere/Top Of Canopy). Supported sensors: QuickBird, Ikonos, WorldView2, Formosat, Spot5, Pleiades, Spot6, Spot7. For other sensors the application also allows providing calibration parameters manually.");
// Documentation
SetDocName("Optical calibration");
SetDocLongDescription("The application allows converting pixel values from DN (for Digital Numbers) to reflectance. Calibrated values are called surface reflectivity and its values lie in the range [0, 1].\nThe first level is called Top Of Atmosphere (TOA) reflectivity. It takes into account the sensor gain, sensor spectral response and the solar illuminations.\nThe second level is called Top Of Canopy (TOC) reflectivity. In addition to sensor gain and solar illuminations, it takes into account the optical thickness of the atmosphere, the atmospheric pressure, the water vapor amount, the ozone amount, as well as the composition and amount of aerosol gasses.\nIt is also possible to indicate an AERONET file which contains atmospheric parameters (version 1 and version 2 of Aeronet file are supported. Note that computing TOC reflectivity will internally compute first TOA and then TOC reflectance. \n"
"\n--------------------------\n\n"
"If the sensor is not supported by the metadata interface factory of OTB, users still have the possibility to give the needed parameters to the application.\n"
......
......@@ -56,7 +56,6 @@ private:
SetDescription("Convert cartographic coordinates to geographic ones.");
// Documentation
SetDocName("Cartographic to geographic coordinates conversion");
SetDocLongDescription("This application computes the geographic coordinates from cartographic ones. User has to give the X and Y coordinate and the cartographic projection (see mapproj parameter for details).");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -55,7 +55,6 @@ private:
SetDescription("Sensor to geographic coordinates conversion.");
// Documentation
SetDocName("Convert Sensor Point To Geographic Point");
SetDocLongDescription("This Application converts a sensor point of an input image to a geographic point using the Forward Sensor Model of the input image.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -62,7 +62,6 @@ private:
SetName("GenerateRPCSensorModel");
SetDescription("Generate a RPC sensor model from a list of Ground Control Points.");
SetDocName("Generate a RPC sensor model");
SetDocLongDescription( "This application generates a RPC sensor model from a list of Ground Control Points. "
"At least 20 points are required for estimation without elevation support, "
"and 40 points for estimation with elevation support. "
......
......@@ -109,7 +109,6 @@ private:
SetName("GridBasedImageResampling");
SetDescription("Resamples an image according to a resampling grid");
SetDocName("Grid Based Image Resampling");
SetDocLongDescription("This application allows performing image resampling from an input resampling grid.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -55,7 +55,6 @@ private:
SetDescription("Extracts an image envelope.");
// Documentation
SetDocName("Image Envelope");
SetDocLongDescription("Build a vector data containing the image envelope polygon. "
"Useful for some projection, you can set the polygon with more points with the sr parameter. "
"This filter supports user-specified output projection. "
......
......@@ -57,7 +57,6 @@ private:
SetDescription("UTM zone determination from a geographic point.");