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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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.txt
*
* 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 "itkUnsharpMaskImageFilter.h"
#include "itkFilterWatcher.h"
#include "itkTestingMacros.h"
int itkUnsharpMaskImageFilterTestSimple( int, char* [] )
{
// Define the dimension of the images
const unsigned int Dimension = 2;
// Define the pixel types of the images
typedef float PixelType;
// Declare the types of the images
typedef itk::Image< PixelType, Dimension > InputImageType;
// Declare the type of the index to access images
typedef itk::Index< Dimension > IndexType;
// Declare the type of the size
typedef itk::Size< Dimension > SizeType;
// Declare the type of the Region
typedef itk::ImageRegion< Dimension > RegionType;
// Create the input image
InputImageType::Pointer inputImage = InputImageType::New();
// Define its size, and start index
SizeType size;
size[0] = 20;
size[1] = 4;
IndexType start;
start.Fill( 0 );
RegionType region;
region.SetIndex( start );
region.SetSize( size );
// Initialize the input image
inputImage->SetLargestPossibleRegion( region );
inputImage->SetBufferedRegion( region );
inputImage->SetRequestedRegion( region );
inputImage->Allocate();
// Declare an Iterator type for the input image
typedef itk::ImageRegionIteratorWithIndex< InputImageType >
InputImageIteratorType;
// Create one iterator for the input Image (this is a light object)
InputImageIteratorType it( inputImage, inputImage->GetRequestedRegion() );
// Initialize the contents of the input image
while( !it.IsAtEnd() )
{
if( it.GetIndex()[0] > itk::IndexValueType(size[0] / 2) )
{
it.Set( 1.0 );
}
else
{
it.Set( 0.0 );
}
++it;
}
// Declare the type for the itk::UnsharpMaskImageFilter
typedef itk::UnsharpMaskImageFilter< InputImageType >
UnsharpMaskImageFilterFilterType;
typedef UnsharpMaskImageFilterFilterType::OutputImageType
GradientImageType;
// Create the filter
UnsharpMaskImageFilterFilterType::Pointer filter =
UnsharpMaskImageFilterFilterType::New();
EXERCISE_BASIC_OBJECT_METHODS(filter, UnsharpMaskImageFilter, ImageToImageFilter);
FilterWatcher watchit( filter );
// Connect the input images
filter->SetInput( inputImage );
UnsharpMaskImageFilterFilterType::InternalPrecisionType threshold = -0.1;
filter->SetThreshold( threshold );
TRY_EXPECT_EXCEPTION( filter->Update() );
// Set the filter properties
UnsharpMaskImageFilterFilterType::SigmaArrayType::ValueType sigma = 2.5;
filter->SetSigma( sigma );
UnsharpMaskImageFilterFilterType::SigmaArrayType sigmas =
filter->GetSigmas();
double tolerance = 10e-6;
for( unsigned int i = 0; i < sigmas.Size(); ++i )
{
UnsharpMaskImageFilterFilterType::SigmaArrayType::ValueType sigma2 =
sigmas[i];
if( !itk::Math::FloatAlmostEqual( sigma, sigma2, 10, tolerance) )
{
std::cerr.precision( static_cast< int >( itk::Math::abs( std::log10( tolerance ) ) ) );
std::cerr << "Test FAILED! ";
std::cerr << "Error in the Sigma values" << std::endl;
std::cerr << "Expected " << sigma << " but got " << sigma2;
std::cerr << " along the [" << i << "]-th dimension." << std::endl;
return EXIT_FAILURE;
}
}
UnsharpMaskImageFilterFilterType::InternalPrecisionType amount = 0.8;
filter->SetAmount( amount );
TEST_SET_GET_VALUE( amount, filter->GetAmount() );
threshold = 0.01;
filter->SetThreshold( threshold );
TEST_SET_GET_VALUE( threshold, filter->GetThreshold() );
bool clamp = itk::NumericTraits<
UnsharpMaskImageFilterFilterType::OutputPixelType >::IsInteger;
filter->SetClamp( clamp );
TEST_SET_GET_VALUE( clamp, filter->GetClamp() );
if( clamp )
{
filter->ClampOn();
TEST_SET_GET_VALUE( true, filter->GetClamp() );
}
else
{
filter->ClampOff();
TEST_SET_GET_VALUE( false, filter->GetClamp() );
}
// Execute the filter
TRY_EXPECT_NO_EXCEPTION( filter->Update() );
// Get the Smart Pointer to the Filter Output
// It is important to do it AFTER the filter is Updated
// Because the object connected to the output may be changed
// by another during GenerateData() call
GradientImageType::Pointer outputImage = filter->GetOutput();
// check that output is correct near the step
start[0] = 9;
float mins[4] = { -0.21f, -0.33f, 1.32f, 1.20f };
float maxs[4] = { -0.20f, -0.32f, 1.33f, 1.21f };
for( unsigned int i = 0; i < 4; i++ )
{
if( outputImage->GetPixel(start) < mins[i]
|| outputImage->GetPixel(start) > maxs[i] )
{
std::cerr << "Test FAILED! Unexpected value: ";
std::cerr << outputImage->GetPixel(start) << std::endl;
std::cerr << "Expected value between " << mins[i];
std::cerr << " and " << maxs[i] << std::endl;
return EXIT_FAILURE;
}
++start[0];
}
// All objects should be automatically destroyed at this point
std::cout << std::endl << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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