/*
* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "otbWrapperApplication.h"
#include "otbWrapperApplicationFactory.h"
#include "otbVectorRescaleIntensityImageFilter.h"
#include "otbUnaryImageFunctorWithVectorImageFilter.h"
#include "otbStreamingShrinkImageFilter.h"
#include "itkListSample.h"
#include "otbListSampleToHistogramListGenerator.h"
#include "itkImageRegionConstIterator.h"
#include "otbImageListToVectorImageFilter.h"
#include "otbMultiToMonoChannelExtractROI.h"
#include "otbImageList.h"
namespace otb
{
namespace Wrapper
{
namespace Functor
{
template< class TScalar >
class ITK_EXPORT LogFunctor
{
public:
LogFunctor(){};
~LogFunctor(){};
TScalar operator() (const TScalar& v) const
{
return vcl_log(v);
}
};
} // end namespace Functor
class Convert : public Application
{
public:
/** Standard class typedefs. */
typedef Convert Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macro */
itkNewMacro(Self);
itkTypeMacro(Convert, otb::Application);
/** Filters typedef */
typedef itk::Statistics::ListSample<FloatVectorImageType::PixelType> ListSampleType;
typedef itk::Statistics::DenseFrequencyContainer2 DFContainerType;
typedef ListSampleToHistogramListGenerator<ListSampleType,
FloatVectorImageType::InternalPixelType,
DFContainerType> HistogramsGeneratorType;
typedef StreamingShrinkImageFilter<FloatVectorImageType,
FloatVectorImageType> ShrinkFilterType;
typedef Functor::LogFunctor<FloatVectorImageType::InternalPixelType> TransferLogFunctor;
typedef UnaryImageFunctorWithVectorImageFilter<FloatVectorImageType,
FloatVectorImageType,
TransferLogFunctor> TransferLogType;
private:
void DoInit() ITK_OVERRIDE
{
SetName("Convert");
SetDescription("Convert an image to a different format, optionally rescaling the data"
" and/or changing the pixel type.");
// Documentation
SetDocName("Image Conversion");
SetDocLongDescription("This application performs an image pixel type conversion "
"(short, ushort, uchar, int, uint, float and double types are handled). "
"The output image is written in the specified format (ie. that corresponds "
"to the given extension).\n The conversion can include a rescale of the data range, "
"by default it's set from 2% to 98% of the data values. The rescale can be linear or log2. \n "
"The choice of the output channels can be done with the extended filename, "
"but less easy to handle. To do this, a 'channels' parameter allows you to select "
"the desired bands at the output. There are 3 modes, the available choices are: \n"
" * grayscale : to display mono image as standard color image \n"
" * rgb : select 3 bands in the input image (multi-bands) \n"
" * all : keep all bands.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
SetDocSeeAlso("Rescale");
AddDocTag(Tags::Manip);
AddDocTag("Conversion");
AddDocTag("Image Dynamic");
AddParameter(ParameterType_InputImage, "in", "Input image");
SetParameterDescription("in", "Input image");
AddParameter(ParameterType_Choice, "type", "Rescale type");
SetParameterDescription("type", "Transfer function for the rescaling");
AddChoice("type.none", "None");
AddChoice("type.linear", "Linear");
AddChoice("type.log2", "Log2");
SetParameterString("type", "none", false);
AddParameter(ParameterType_Float,"type.linear.gamma","Gamma correction factor");
SetParameterDescription("type.linear.gamma","Gamma correction factor");
SetDefaultParameterFloat("type.linear.gamma",1.0);
MandatoryOff("type.linear.gamma");
AddParameter(ParameterType_InputImage, "mask", "Input mask");
SetParameterDescription("mask", "The masked pixels won't be used to adapt the dynamic "
"(the mask must have the same dimensions as the input image)");
MandatoryOff("mask");
DisableParameter("mask");
AddParameter(ParameterType_Group,"hcp","Histogram Cutting Parameters");
SetParameterDescription("hcp","Parameters to cut the histogram edges before rescaling");
AddParameter(ParameterType_Float, "hcp.high", "High Cut Quantile");
SetParameterDescription("hcp.high", "Quantiles to cut from histogram high values "
"before computing min/max rescaling (in percent, 2 by default)");
MandatoryOff("hcp.high");
SetDefaultParameterFloat("hcp.high", 2.0);
DisableParameter("hcp.high");
AddParameter(ParameterType_Float, "hcp.low", "Low Cut Quantile");
SetParameterDescription("hcp.low", "Quantiles to cut from histogram low values "
"before computing min/max rescaling (in percent, 2 by default)");
MandatoryOff("hcp.low");
SetDefaultParameterFloat("hcp.low", 2.0);
DisableParameter("hcp.low");
AddParameter(ParameterType_OutputImage, "out", "Output Image");
SetParameterDescription("out", "Output image");
SetDefaultOutputPixelType("out",ImagePixelType_uint8);
AddParameter(ParameterType_Choice, "channels", "Channels selection");
SetParameterDescription("channels", "It's possible to select the channels "
"of the output image. There are 3 modes, the available choices are:");
AddChoice("channels.all", "Default mode");
SetParameterDescription("channels.all", "Select all bands in the input image, (1,...,n).");
AddChoice("channels.grayscale", "Grayscale mode");
SetParameterDescription("channels.grayscale", "Display single channel as standard color image.");
AddParameter(ParameterType_Int, "channels.grayscale.channel", "Grayscale channel");
SetDefaultParameterInt("channels.grayscale.channel", 1);
SetMinimumParameterIntValue("channels.grayscale.channel", 1);
AddChoice("channels.rgb", "RGB composition");
SetParameterDescription("channels.rgb", "Select 3 bands in the input image "
"(multi-bands), by default (1,2,3).");
AddParameter(ParameterType_Int, "channels.rgb.red", "Red Channel");
SetParameterDescription("channels.rgb.red", "Red channel index.");
SetMinimumParameterIntValue("channels.rgb.red", 1);
AddParameter(ParameterType_Int, "channels.rgb.green", "Green Channel");
SetParameterDescription("channels.rgb.green", "Green channel index.");
SetMinimumParameterIntValue("channels.rgb.green", 1);
AddParameter(ParameterType_Int, "channels.rgb.blue", "Blue Channel");
SetParameterDescription("channels.rgb.blue", "Blue channel index.");
SetMinimumParameterIntValue("channels.rgb.blue", 1);
AddRAMParameter();
// Doc example parameter settings
SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_XS.tif");
SetDocExampleParameterValue("out", "otbConvertWithScalingOutput.png");
SetDocExampleParameterValue("type", "linear");
SetDocExampleParameterValue("channels", "rgb");
SetOfficialDocLink();
}
void DoUpdateParameters() ITK_OVERRIDE
{
// Read information
typedef otb::ImageMetadataInterfaceBase ImageMetadataInterfaceType;
ImageMetadataInterfaceType::Pointer metadataInterface =
ImageMetadataInterfaceFactory::CreateIMI(GetParameterImage("in")->GetMetaDataDictionary());
int nbBand = GetParameterImage("in")->GetNumberOfComponentsPerPixel();
SetMaximumParameterIntValue("channels.grayscale.channel", nbBand);
SetMaximumParameterIntValue("channels.rgb.red", nbBand);
SetMaximumParameterIntValue("channels.rgb.green", nbBand);
SetMaximumParameterIntValue("channels.rgb.blue", nbBand);
if (nbBand > 1)
{
// get band index : Red/Green/Blue
int bandRed = metadataInterface->GetDefaultDisplay()[0];
int bandGreen = metadataInterface->GetDefaultDisplay()[1];
int bandBlue = metadataInterface->GetDefaultDisplay()[2];
SetDefaultParameterInt("channels.rgb.red", bandRed);
SetDefaultParameterInt("channels.rgb.green", bandGreen);
SetDefaultParameterInt("channels.rgb.blue", bandBlue);
}
}
template<class TImageType>
void GenericDoExecute()
{
std::string rescaleType = this->GetParameterString("type");
if( (rescaleType != "none") && (rescaleType != "linear") && (rescaleType != "log2") )
{
itkExceptionMacro("Unknown rescale type "<<rescaleType<<".");
}
if( rescaleType == "none" )
{
// selected channel
typename TImageType::Pointer tempImage;
tempImage = GetSelectedChannels<TImageType>();
SetParameterOutputImage<TImageType>("out", tempImage);
}
else // linear or log2
{
FloatVectorImageType::Pointer mask;
if (IsParameterEnabled("mask")) mask = this->GetParameterImage("mask");
// selected channel
typename FloatVectorImageType::Pointer tempImage;
tempImage = GetSelectedChannels<FloatVectorImageType>();
const unsigned int nbComp(tempImage->GetNumberOfComponentsPerPixel());
typedef otb::VectorRescaleIntensityImageFilter<FloatVectorImageType, TImageType> RescalerType;
typename TImageType::PixelType minimum;
typename TImageType::PixelType maximum;
minimum.SetSize(nbComp);
maximum.SetSize(nbComp);
minimum.Fill( itk::NumericTraits<typename TImageType::InternalPixelType>::min() );
maximum.Fill( itk::NumericTraits<typename TImageType::InternalPixelType>::max() );
typename RescalerType::Pointer rescaler = RescalerType::New();
rescaler->SetOutputMinimum(minimum);
rescaler->SetOutputMaximum(maximum);
// We need to subsample the input image in order to estimate its
// histogram
typename ShrinkFilterType::Pointer shrinkFilter = ShrinkFilterType::New();
// Shrink factor is computed so as to load a quicklook of 1000
// pixels square at most
typename FloatVectorImageType::SizeType imageSize = tempImage->GetLargestPossibleRegion().GetSize();
unsigned int shrinkFactor =
std::max(imageSize[0], imageSize[1]) < 1000 ? 1 : std::max(imageSize[0], imageSize[1])/1000;
otbAppLogDEBUG( << "Shrink factor used to compute Min/Max: "<<shrinkFactor );
otbAppLogDEBUG( << "Shrink starts..." );
shrinkFilter->SetShrinkFactor(shrinkFactor);
shrinkFilter->GetStreamer()->SetAutomaticAdaptativeStreaming(GetParameterInt("ram"));
AddProcess(shrinkFilter->GetStreamer(), "Computing shrink Image for min/max estimation...");
if ( rescaleType == "log2")
{
//define the transfer log
m_TransferLog = TransferLogType::New();
m_TransferLog->SetInput(tempImage);
m_TransferLog->UpdateOutputInformation();
shrinkFilter->SetInput(m_TransferLog->GetOutput());
rescaler->SetInput(m_TransferLog->GetOutput());
shrinkFilter->Update();
}
else
{
shrinkFilter->SetInput(tempImage);
rescaler->SetInput(tempImage);
shrinkFilter->Update();
}
ShrinkFilterType::Pointer maskShrinkFilter = ShrinkFilterType::New();
otbAppLogDEBUG( << "Evaluating input Min/Max..." );
itk::ImageRegionConstIterator<FloatVectorImageType>
it(shrinkFilter->GetOutput(), shrinkFilter->GetOutput()->GetLargestPossibleRegion());
itk::ImageRegionConstIterator<FloatVectorImageType> itMask;
typename ListSampleType::Pointer listSample = ListSampleType::New();
listSample->SetMeasurementVectorSize(tempImage->GetNumberOfComponentsPerPixel());
// Now we generate the list of samples
if (IsParameterEnabled("mask"))
{
maskShrinkFilter->SetShrinkFactor(shrinkFactor);
maskShrinkFilter->SetInput(mask);
maskShrinkFilter->GetStreamer()->SetAutomaticAdaptativeStreaming(GetParameterInt("ram"));
maskShrinkFilter->Update();
itMask = itk::ImageRegionConstIterator<FloatVectorImageType>(
maskShrinkFilter->GetOutput(),maskShrinkFilter->GetOutput()->GetLargestPossibleRegion());
// Remove masked pixels
it.GoToBegin();
itMask.GoToBegin();
while (!it.IsAtEnd())
{
// float values, so the threshold is set to 0.5
if (itMask.Get()[0] < 0.5)
{
listSample->PushBack(it.Get());
}
++it;
++itMask;
}
if (listSample->Size() == 0)
{
otbAppLogINFO( << "All pixels were masked, the application assume a wrong mask "
"and include all the image");
}
}
// if mask is disable and all pixels were masked
if ((!IsParameterEnabled("mask")) || (listSample->Size() == 0))
{
for(it.GoToBegin(); !it.IsAtEnd(); ++it)
{
listSample->PushBack(it.Get());
}
}
// And then the histogram
typename HistogramsGeneratorType::Pointer histogramsGenerator = HistogramsGeneratorType::New();
histogramsGenerator->SetListSample(listSample);
histogramsGenerator->SetNumberOfBins(255);
histogramsGenerator->NoDataFlagOn();
histogramsGenerator->Update();
// And extract the lower and upper quantile
typename FloatVectorImageType::PixelType inputMin(nbComp), inputMax(nbComp);
auto histOutput = histogramsGenerator->GetOutput();
assert(histOutput);
for(unsigned int i = 0; i < nbComp; ++i)
{
auto && elm = histOutput->GetNthElement(i);
assert(elm);
inputMin[i] = elm->Quantile(0, 0.01 * GetParameterFloat("hcp.low"));
inputMax[i] = elm->Quantile(0, 1.0 - 0.01 * GetParameterFloat("hcp.high"));
}
otbAppLogDEBUG( << std::setprecision(5) << "Min/Max computation done : min=" << inputMin
<< " max=" << inputMax );
rescaler->AutomaticInputMinMaxComputationOff();
rescaler->SetInputMinimum(inputMin);
rescaler->SetInputMaximum(inputMax);
if ( rescaleType == "linear")
{
rescaler->SetGamma(GetParameterFloat("type.linear.gamma"));
}
m_TmpFilter = rescaler;
SetParameterOutputImage<TImageType>("out", rescaler->GetOutput());
}
}
// Get the bands order
std::vector<int> GetChannels()
{
std::vector<int> channels;
int nbChan = GetParameterImage("in")->GetNumberOfComponentsPerPixel();
std::string channelMode = GetParameterString("channels");
if(channelMode == "grayscale")
{
if (GetParameterInt("channels.grayscale.channel") <= nbChan)
{
channels = {GetParameterInt("channels.grayscale.channel"),
GetParameterInt("channels.grayscale.channel"),
GetParameterInt("channels.grayscale.channel")};
}
else
{
itkExceptionMacro(<< "The channel has an invalid index");
}
}
else if (channelMode == "rgb")
{
if ((GetParameterInt("channels.rgb.red") <= nbChan)
&& ( GetParameterInt("channels.rgb.green") <= nbChan)
&& ( GetParameterInt("channels.rgb.blue") <= nbChan))
{
channels = {GetParameterInt("channels.rgb.red"),
GetParameterInt("channels.rgb.green"),
GetParameterInt("channels.rgb.blue")};
}
else
{
itkExceptionMacro(<< "At least one needed channel has an invalid index");
}
}
else if (channelMode == "all")
{
// take all bands
channels.resize(nbChan);
std::iota(channels.begin(), channels.end(), 1);
}
return channels;
}
// return an image with the bands order modified of the input image
template<class TImageType>
typename TImageType::Pointer GetSelectedChannels()
{
typedef MultiToMonoChannelExtractROI<FloatVectorImageType::InternalPixelType,
typename TImageType::InternalPixelType> ExtractROIFilterType;
typedef ObjectList<ExtractROIFilterType> ExtractROIFilterListType;
typedef otb::ImageList<otb::Image<typename TImageType::InternalPixelType> > ImageListType;
typedef ImageListToVectorImageFilter<ImageListType,
TImageType > ListConcatenerFilterType;
typename ImageListType::Pointer imageList;
typename ListConcatenerFilterType::Pointer concatener;
typename ExtractROIFilterListType::Pointer extractorList;
imageList = ImageListType::New();
concatener = ListConcatenerFilterType::New();
extractorList = ExtractROIFilterListType::New();
const bool monoChannel = IsParameterEnabled("channels.grayscale");
// get band order
std::vector<int> channels = GetChannels();
for (auto && channel : channels)
{
typename ExtractROIFilterType::Pointer extractROIFilter = ExtractROIFilterType::New();
extractROIFilter->SetInput(GetParameterImage("in"));
if (!monoChannel) extractROIFilter->SetChannel(channel);
extractROIFilter->UpdateOutputInformation();
extractorList->PushBack(extractROIFilter);
imageList->PushBack(extractROIFilter->GetOutput());
}
concatener->SetInput(imageList);
concatener->UpdateOutputInformation();
concatener->Update();
return concatener->GetOutput();
}
void DoExecute() ITK_OVERRIDE
{
switch ( this->GetParameterOutputImagePixelType("out") )
{
case ImagePixelType_uint8:
GenericDoExecute<UInt8VectorImageType>();
break;
case ImagePixelType_int16:
GenericDoExecute<Int16VectorImageType>();
break;
case ImagePixelType_uint16:
GenericDoExecute<UInt16VectorImageType>();
break;
case ImagePixelType_int32:
GenericDoExecute<Int32VectorImageType>();
break;
case ImagePixelType_uint32:
GenericDoExecute<UInt32VectorImageType>();
break;
case ImagePixelType_float:
GenericDoExecute<FloatVectorImageType>();
break;
case ImagePixelType_double:
GenericDoExecute<DoubleVectorImageType>();
break;
default:
itkExceptionMacro("Unknown pixel type "<<this->GetParameterOutputImagePixelType("out")<<".");
break;
}
}
itk::ProcessObject::Pointer m_TmpFilter;
TransferLogType::Pointer m_TransferLog;
};
}
}
OTB_APPLICATION_EXPORT(otb::Wrapper::Convert)