image::ArrayGrid<int>* MedianFilter::RunMedian( image::ArrayGrid<int>* pGridIn, int mySize)
{
int windowWidth = 2 * mySize + 1;
int windowArea = windowWidth * windowWidth;
int medianPosition = (int)(windowArea / 2);
int width = pGridIn->GetWidth();
int height = pGridIn->GetHeight();
int *pR = new int [windowArea];
ArrayGrid<int>* pGridOut = pGridIn->Clone();
for (int y = mySize; y < height - mySize; y++)
{
for (int x = mySize; x < width - mySize; x ++)
{
int myIndex=0;
for (int s = -mySize; s <= mySize; s++)
{
for (int t = -mySize; t <= mySize; t++)
{
pR[myIndex] = pGridIn->GetValue( x+s, y+t );
myIndex++;
}
}
qsort( pR, windowArea, sizeof(int), MathUtils::CompareIntegers );
pGridOut->SetValue( x, y, pR[ medianPosition ] );
}
}
delete [] pR;
return pGridOut;
}
void PyramidDenoiser::DenoiseLevelLaplacian(int level)
{
if (level < (int)(mpPyramid->GetNumberOfScales() - 1))
{
PyramidLevel<double>* pBandSet;
if (level != -1)
{
pBandSet = mpPyramid->GetRecursiveScale(level);
}
else
{
pBandSet = mpPyramid->GetResidualScale();
}
for (int orientationIndex = 0; orientationIndex < pBandSet->GetNumberOfOrientations(); orientationIndex++)
{
ArrayGrid<double>* pBand = pBandSet->GetOrientedBand( orientationIndex);
for (int y = 0; y < pBand->GetHeight(); y++)
{
for (int x = 0; x < pBand->GetWidth(); x++)
{
double sigmaSignal = EstimateSigmaSignal( pBand, x, y, mSigmaNoise, mWindowSize );
double w1 = pBand->GetValue(x,y);
double shrinkageFactor = ComputeLaplacianShrinkagefactor(w1, sigmaSignal, mSigmaNoise);
mpPyramid->GetRecursiveScale( level)->GetOrientedBand( orientationIndex)->SetValue(x,y, shrinkageFactor * w1);
}
}
}
}
else
{
std::cerr << "PyramidDenoiser::DenoiseLevelLaplacian: Cannot denoise level " << level << " since top level is " << mpPyramid->GetNumberOfScales() << std::endl << std::flush;
}
}
ArrayGrid<double>* WienerDeconvolve::EstimateIdealSpectrum( FFTBand* pFFTInputGrid, FFTBand* pFFTPSFGrid, double noiseLevel )
{
int width = pFFTInputGrid->GetWidth();
int height = pFFTInputGrid->GetHeight();
bool needInitialisation = true;
double initialRealValue = 0.0;
ArrayGrid<double>* pEstimatedIdealSpectrum = new ArrayGrid<double>( width, height, needInitialisation, initialRealValue );
double fourierNoiseLevel = width * height * noiseLevel * noiseLevel;
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double spectrumDegraded = std::norm( pFFTInputGrid->GetValue( x, y ) ); // norm is square of magnitude
double spectrumPsf = std::norm( pFFTPSFGrid->GetValue( x, y ) ); // norm is square of magnitude
double estimatedValue = THRESHOLD;
double differenceValue = spectrumDegraded - fourierNoiseLevel;
if (( spectrumPsf > THRESHOLD) && (differenceValue > 0.0 ))
{
estimatedValue = differenceValue / spectrumPsf;
}
pEstimatedIdealSpectrum->SetValue( x, y, estimatedValue );
}
}
ArrayGrid<double>* pSmoothSpectrum = GaussConvolve::ConvolveSeparable(pEstimatedIdealSpectrum, 1.5);
delete pEstimatedIdealSpectrum;
return pSmoothSpectrum;
}
image::ArrayGrid<bool>* PyramidKeyPointDetector::FindLocalMaxima( ArrayGrid<double>* pGrid )
{
int size = 5;
int width = pGrid->GetWidth();
int height = pGrid->GetHeight();
bool needsInitialisation = true;
double initialValue = false;
ArrayGrid<bool>* pKeyPointsMap = new ArrayGrid<bool>( width, height, needsInitialisation, initialValue );
pKeyPointsMap->SetGridValues( false );
for (int y = size; y < height-size; y++)
{
for (int x = size; x < width-size; x++)
{
bool isLocalMaximum = true;
for (int dy = -size; dy <= size; dy++)
{
for (int dx = -size; dx <= size; dx++)
{
if ( (dx != 0) || (dy != 0) )
{
if (pGrid->GetValue(x+dx, y+dy) >= pGrid->GetValue(x, y))
{
isLocalMaximum = false;
}
}
}
}
pKeyPointsMap->SetValue(x, y, isLocalMaximum);
}
}
return pKeyPointsMap;
}
void PyramidKeyPointDetector::AccumulateScales( )
{
int nrScalesToAccumulate = mvEnergyMaps.size();
int width = mvEnergyMaps[0]->GetWidth();
int height = mvEnergyMaps[0]->GetHeight();
bool needsInitialisation = true;
double initialValue = 0.0;
ArrayGrid<double>* pAccumulate = new ArrayGrid<double>( width, height, needsInitialisation, initialValue );
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double tmpValue = 0.0;
for (int scale = 0; scale < nrScalesToAccumulate; scale++)
{
tmpValue += mvEnergyMaps[scale]->GetValue(x, y);
}
pAccumulate->SetValue(x, y, tmpValue);
}
}
mvAccumulatedMaps.push_back( pAccumulate );
int scaleID = nrScalesToAccumulate;
stringstream ss;
ss << "AccumulatedEnergy-" << scaleID << ".pgm";
ImageIO::WritePGM( pAccumulate, ss.str(), ImageIO::NORMAL_OUT );
ArrayGrid<bool>* pKeyPointsMap = FindLocalMaxima( pAccumulate );
stringstream ss1;
ss1 << "KeyPointMap-" << scaleID << ".pgm";
ImageIO::WritePGM( pKeyPointsMap, ss1.str() );
}
bool PyramidKeyPointDetector::MergeOrientations1( int scale )
{
ArrayGrid<double>* pEnergyMap = 0;
ArrayGrid<double>* pUpscaledEnergyMap = 0;
PyramidLevel< std::complex< double > >* pPyrLevel = 0;
if (scale >= 0)
{
pPyrLevel = mpPyramid->GetRecursiveScale( scale );
}
else
{
pPyrLevel = mpPyramid->GetResidualScale( );
}
int width = pPyrLevel->GetWidth();
int height = pPyrLevel->GetHeight();
bool needsInitialisation = true;
double initialValue = 0.0;
pEnergyMap = new ArrayGrid<double>( width, height, needsInitialisation, initialValue );
int nrOrientations = mpPyramid->GetNumberOfOrientations();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double tmpValue = 0.0;
for (int i = 0; i < nrOrientations-1; i++)
{
for (int j = i+1; j < nrOrientations; j++)
{
if ( ( abs( i - j ) > 1 ) && ( abs( i - j%(nrOrientations-1) ) > 0) )
{
tmpValue += ( abs( pPyrLevel->GetOrientedBand( i )->GetValue(x, y) )
* abs( pPyrLevel->GetOrientedBand( j )->GetValue(x, y) )
);
}
}
}
pEnergyMap->SetValue( x, y, tmpValue);
}
}
if (scale > 0)
{
pUpscaledEnergyMap = GaussConvolve::UpsampleGaussianInterpolated( pEnergyMap, MathUtils::ComputeIntegerPower(2, scale ) );
delete pEnergyMap;
}
else
{
pUpscaledEnergyMap = pEnergyMap;
}
mvEnergyMaps.push_back( pUpscaledEnergyMap );
return true;
}
bool ReadPgmFromZipFileTest()
{
std::string zipName = std::string("/u/frooms/research/develop/stira-env/stira/testdata/testZipFile.zip");
std::string imageInZipName = std::string("CropOrig-2033.pgm");
ArrayGrid<int>* pGrid = ImageIO::ReadPGMfromZip( zipName, imageInZipName );
cout << "Image from zip: width = " << pGrid->GetWidth() << " height = " << pGrid->GetHeight() << endl << flush;
ImageIO::WritePGM( pGrid, std::string("ImageFromZip.pgm") );
delete pGrid;
return true;
}
bool TestEmptyPlusGaussianNoise( int width, int height, double intensity, double sigma )
{
ArrayGrid<double>* pGrid = new ArrayGrid<double>( width, height );
Random rn;
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
pGrid->SetValue(x, y, (intensity + rn.normal( 0.0, sigma )) );
}
}
double testMean = GridStatistics<double>::GetGridMean( pGrid );
double testVariance = GridStatistics<double>::GetGridVariance( pGrid, testMean );
double testKurtosis = GridStatistics<double>::GetGridKurtosis( pGrid, testMean, testVariance );
if ( fabs( sqrt( testVariance ) - sigma ) > 0.1 )
{
cout << "mean intensity: theoretically = " << intensity << "\t estimated = " << testMean << " too different!!" << endl << flush;
delete pGrid;
return false;
}
if ( fabs( intensity - testMean ) > 0.1 )
{
cout << "variance: theoretically = " << sigma * sigma << " \t estimated = " << testVariance << " too different!!" << endl << flush;
delete pGrid;
return false;
}
if ( fabs( testKurtosis ) > 0.1 )
{
cout << "Kurtosis " << testKurtosis << " too large (should be close to 0 for Gaussian noise)!!" << endl << flush;
delete pGrid;
return false;
}
cout << "Mean : theoretically = " << intensity << " \t estimated = " << testMean << " \t -> OK!" << endl << flush;
cout << "variance : theoretically = " << sigma * sigma << " \t estimated = " << testVariance << " \t -> OK!" << endl << flush;
cout << "Kurtosis : " << testKurtosis << ", is close to 0 \t\t\t -> OK!" << endl << flush;
delete pGrid;
return true;
}
void PyramidDenoiser::DenoiseLevelBivariate(int level)
{
if (level < (int)(mpPyramid->GetNumberOfScales() - 1))
{
PyramidLevel<double>* pBandSetCurrent;
PyramidLevel<double>* pBandSetParent;
if (level != -1)
{
pBandSetCurrent = mpPyramid->GetRecursiveScale(level);
pBandSetParent = mpPyramid->GetRecursiveScale(level+1);
}
else
{
pBandSetCurrent = mpPyramid->GetResidualScale();
pBandSetParent = mpPyramid->GetRecursiveScale(0);
}
double avgVariance = 0.0;
double scaleNoiseVariance = mSigmaNoise / GetScaledNoiseVarianceFactor( level );
double scaleParentChildFactor = GetScaledParentChildFactor( level);
for (int orientationIndex = 0; orientationIndex < pBandSetCurrent->GetNumberOfOrientations(); orientationIndex++)
{
ArrayGrid<double>* pBandCurrent = pBandSetCurrent->GetOrientedBand( orientationIndex);
ArrayGrid<double>* pBandParent = pBandSetParent->GetOrientedBand( orientationIndex);
double meanVal = GridStatistics<double>::GetGridMean( pBandCurrent );
double varianceVal = GridStatistics<double>::GetGridVariance( pBandCurrent, meanVal );
#ifdef DEBUG
cout << "Denoising level " << level << " and orientationIndex " << orientationIndex
<< ", variance is " << varianceVal << " and scaled noise variance = " << scaleNoiseVariance << endl << flush;
#endif
avgVariance += varianceVal;
for (int y = 0; y < pBandCurrent->GetHeight(); y++)
{
for (int x = 0; x < pBandCurrent->GetWidth(); x++)
{
double sigmaSignal = EstimateSigmaSignal( pBandCurrent, x, y, mSigmaNoise, mWindowSize );
double w1 = pBandCurrent->GetValue(x,y);
double w2 = pBandParent->GetValue(x/2,y/2) / scaleParentChildFactor;
double shrinkageFactor = ComputeBivariateShrinkagefactor(w1, w2, sigmaSignal, scaleNoiseVariance );
pBandCurrent->SetValue(x,y, shrinkageFactor * w1);
}
}
}
#ifdef DEBUG
cout << "Average variance at scale level = " << (avgVariance) / (double)(pBandSetCurrent->GetNumberOfOrientations())
<< endl << flush;
#endif
}
else
{
std::cerr << "PyramidDenoiser::DenoiseLevelBivariate: Cannot denoise level " << level << " since top level is " << mpPyramid->GetNumberOfScales() << std::endl << std::flush;
}
}
ArrayGrid<double>* WienerDeconvolve::RunSingleband( ArrayGrid<double>* pInGrid, ArrayGrid<double>* pInPSF, double noiseLevel )
{
int width = pInGrid->GetWidth();
int height = pInGrid->GetHeight();
FFTBand* pFFTInputGrid = new FFTBand( pInGrid );
FFTBand* pFFTPSFGrid = new FFTBand( pInPSF );
FFTBand* pWienerOut = new FFTBand( pInGrid );
pFFTInputGrid->ApplyForwardTransform();
pFFTPSFGrid->ApplyForwardTransform();
ArrayGrid<double>* pEstimatedIdealSpectrum = EstimateIdealSpectrum( pFFTInputGrid, pFFTPSFGrid, noiseLevel );
double fourierNoiseLevel = width * height * noiseLevel * noiseLevel;
pFFTPSFGrid->Conjugate();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
complex<double> wienerEstimate =
( ( pFFTPSFGrid->GetValue(x, y) * pFFTInputGrid->GetValue(x, y) )
/ ( POWER2( abs( pFFTPSFGrid->GetValue( x, y ) ) )
+ ( fourierNoiseLevel / pEstimatedIdealSpectrum->GetValue(x, y) )
)
);
wienerEstimate /= (width * height);
pWienerOut->SetValue( x, y, wienerEstimate );
}
}
pWienerOut->ApplyInverseTransform();
ArrayGrid<double>* pRestoredGrid = pWienerOut->ConvertToRealGrid();
delete pEstimatedIdealSpectrum;
delete pFFTInputGrid;
delete pFFTPSFGrid;
delete pWienerOut;
return pRestoredGrid;
}
ArrayGrid<double>* DistanceTransform::Run( ArrayGrid<double> *pGridIn)
{
int width = pGridIn->GetWidth();
int height = pGridIn->GetHeight();
ArrayGrid<double> *pGridOut = new ArrayGrid<double>(width, height, false, 0.0);
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
if (pGridIn->GetValue(x, y) > 245 ) // objects of interest to compute distance to
{
pGridOut->SetValue(x, y, 0);
}
else // image background
{
pGridOut->SetValue( x, y, STIRA_INFINITE);
}
}
}
DistanceTransform2D( pGridOut );
return pGridOut;
}
image::ArrayGrid<double>* MedianFilter::RunMedian( image::ArrayGrid<double>* pGridIn, int size)
{
int windowWidth = 2 * size + 1;
int windowArea = windowWidth * windowWidth;
int medianPosition = (int)(windowArea / 2);
int width = pGridIn->GetWidth();
int height = pGridIn->GetHeight();
double* pR = new double[windowArea];
ArrayGrid<double>* pGridOut = pGridIn->Clone();
//cout << "Input grid has width " << pGridIn->GetWidth() << " and height " << pGridIn->GetHeight() << endl;
for (int y = size; y < height-size; y++)
{
for (int x = size; x < width - size; x ++)
{
int index=0;
for (int s = -size; s <= size; s++)
{
for (int t = -size; t <= size; t++)
{
pR[index] = pGridIn->GetValue( x+s, y+t );
index++;
}
}
qsort( pR, windowArea, sizeof(double), MathUtils::CompareDoubles );
pGridOut->SetValue( x, y, pR[medianPosition] );
}
}
delete [] pR;
cout << "Output grid has width " << pGridOut->GetWidth() << " and height " << pGridOut-> GetHeight() << endl;
return pGridOut;
}
ArrayGrid<double>* PyramidBurtAdelson::DecomposeSingleScale( ArrayGrid<double>* pGridIn, int scale )
{
// smoothened input
ArrayGrid<double>* pLowpassTmp = mSeparableFilter->RunRowColumn( pGridIn, pH, pH, 5, 5 );
// smoothened and downsampled input
ArrayGrid<double>* pNextLowpass = ArrayGridTools<double>::DownSampleGrid( pLowpassTmp );
delete pLowpassTmp;
// upsample again to subtract from original input
int currentScaleWidth = pNextLowpass->GetWidth();
int currentScaleHeight = pNextLowpass->GetHeight();
ArrayGrid<double>* pUpscaleTmp = ArrayGridTools<double>::UpSampleGrid( pNextLowpass, currentScaleWidth * 2, currentScaleHeight * 2 );
ArrayGrid<double>* pUpscale2 = mSeparableFilter->RunRowColumn( pUpscaleTmp, pH, pH, 5, 5 );
delete pUpscaleTmp;
pGridIn->SubtractGrid(pUpscale2);
delete pUpscale2;
mpPyramid->GetRecursiveScale( scale )->AddOrientedBand( pGridIn );
return pNextLowpass;
}
Image* AnisotropicDiffusion::Run()
{
for (int bandNr = 0; bandNr < mpSourceImage->GetNumberOfBands(); bandNr++)
{
cout << "Processing band nr " << bandNr << endl << flush;
for (int iterationNr = 0; iterationNr < mMaxNumberOfIterations; iterationNr++)
{
cout << "\t\t iteration nr " << iterationNr << flush;
ArrayGrid<double>* pPreviousIterationGrid = mpSourceImage->GetBands()[bandNr]->Clone();
double flowConstant = DetermineMeanGradient( pPreviousIterationGrid ) * mFlowFactor;
cout << "\t\t FlowConstant = " << flowConstant << endl << flush;
for (int y = 1; y < mpSourceImage->GetHeight()-1; y++)
{
for (int x=1; x < mpSourceImage->GetWidth()-1 ; x++)
{
double deltaIxu, deltaIxl, deltaIyu, deltaIyl;
double cxu, cxl, cyu, cyl, deltaI, ttmp;
deltaIxu = pPreviousIterationGrid->GetValue(x+1, y) - pPreviousIterationGrid->GetValue(x, y);
deltaIxl = pPreviousIterationGrid->GetValue(x, y) - pPreviousIterationGrid->GetValue(x-1, y);
deltaIyu = pPreviousIterationGrid->GetValue(x, y+1) - pPreviousIterationGrid->GetValue(x, y);
deltaIyl = pPreviousIterationGrid->GetValue(x, y) - pPreviousIterationGrid->GetValue(x, y-1);
cxu = 1.0 / (1.0 + pow( ( abs( deltaIxu) / flowConstant ), (1.8) ) );
cxl = 1.0 / (1.0 + pow( ( abs( deltaIxl) / flowConstant ), (1.8) ) );
cyu = 1.0 / (1.0 + pow( ( abs( deltaIyu) / flowConstant ), (1.8) ) );
cyl = 1.0 / (1.0 + pow( ( abs( deltaIyl) / flowConstant ), (1.8) ) );
deltaI= (cxu*deltaIxu-cxl*deltaIxl)+(cyu*deltaIyu-cyl*deltaIyl);
ttmp = pPreviousIterationGrid->GetValue(x,y) + mDeltaT * deltaI;
mpSourceImage->GetBands()[bandNr]->SetValue(x,y,ttmp);
} //for x
}//for y
delete pPreviousIterationGrid;
} //for iterationNr
} // for bandNr
return mpSourceImage;
}
void TestDrawFigure()
{
int width = 512;
int height = 512;
ArrayGrid<int>* pGrid = new ArrayGrid<int>( width, height );
std::vector< Point<int> > vCorners;
Point<int> p1(129, 52); vCorners.push_back( p1 );
Point<int> p2(234, 32); vCorners.push_back( p2 );
Point<int> p3(356, 51); vCorners.push_back( p3 );
Point<int> p4(267, 248); vCorners.push_back( p4 );
Point<int> p5(100, 156); vCorners.push_back( p5 );
pGrid->SetValue( DrawFigures::DrawPolygon( vCorners ), 250 );
Point<int> testPointOut( 60, 240 );
pGrid->SetValue( testPointOut.GetX(), testPointOut.GetY(), 250 );
pGrid->SetValue( testPointOut.GetX()-1, testPointOut.GetY(), 250 );
pGrid->SetValue( testPointOut.GetX()+1, testPointOut.GetY(), 250 );
pGrid->SetValue( testPointOut.GetX(), testPointOut.GetY()-1, 250 );
pGrid->SetValue( testPointOut.GetX(), testPointOut.GetY()+1, 250 );
ImageIO::WritePGM( pGrid, std::string("Polygon.pgm"), ImageIO::NULL_OUT );
bool testRes1 = DrawFigures::IsPointInPolygon( vCorners, testPointOut );
cout << "Test point 1 in polygon = " << testRes1 << endl << flush;
Point<int> testPointIn( 226, 126 );
pGrid->SetValue( testPointIn.GetX(), testPointIn.GetY(), 250 );
pGrid->SetValue( testPointIn.GetX()-1, testPointIn.GetY(), 250 );
pGrid->SetValue( testPointIn.GetX()+1, testPointIn.GetY(), 250 );
pGrid->SetValue( testPointIn.GetX(), testPointIn.GetY()-1, 250 );
pGrid->SetValue( testPointIn.GetX(), testPointIn.GetY()+1, 250 );
ImageIO::WritePGM( pGrid, std::string("Polygon.pgm"), ImageIO::NULL_OUT );
bool testRes2 = DrawFigures::IsPointInPolygon( vCorners, testPointIn );
cout << "Test point 2 in polygon = " << testRes2 << endl << flush;
delete pGrid;
}
bool CriticallySubsampledTransform::Reconstruct( double threshold )
{
ArrayGrid<double>* pRecursiveInput = mpPyramid->GetLowpassResidual( );
for ( mCurrentScale = mNrScales-1; mCurrentScale >= 0; mCurrentScale-- )
{
int width = pRecursiveInput->GetWidth();
int height = pRecursiveInput->GetHeight();
int upScaledWidth = width * 2;
int upScaledHeight = height * 2;
bool needsInitialisation = true;
double initialValue = 0.0;
ArrayGrid<double>* pLLGrid = new ArrayGrid<double>( upScaledWidth, upScaledHeight, needsInitialisation, initialValue );
for (int y = 0; y < upScaledHeight; y+=2)
{
for (int x = 0; x < upScaledWidth; x+=2)
{
int halfX = x/2;
int halfY = y/2;
double x00 = pRecursiveInput->GetValue( halfX, halfY );
double x01 = mpPyramid->GetRecursiveScale( mCurrentScale )->GetOrientedBand( 0 )->GetValue( halfX, halfY );
double x10 = mpPyramid->GetRecursiveScale( mCurrentScale )->GetOrientedBand( 1 )->GetValue( halfX, halfY );
double x11 = mpPyramid->GetRecursiveScale( mCurrentScale )->GetOrientedBand( 2 )->GetValue( halfX, halfY );
pLLGrid->SetValue( x , y , (x00 + x01 + x10 + x11) / 2.0 );
pLLGrid->SetValue( x , y+1, (x00 + x01 - x10 - x11) / 2.0 );
pLLGrid->SetValue( x+1, y , (x00 - x01 + x10 - x11) / 2.0 );
pLLGrid->SetValue( x+1, y+1, (x00 - x01 - x10 + x11) / 2.0 );
}
}
pRecursiveInput = pLLGrid->Clone(); delete pLLGrid;
}
mpDecomposeReconstructGrid = pRecursiveInput;
return true;
}
bool CriticallySubsampledTransform::Decompose( image::ArrayGrid<double>* pSourceGrid, int nrScales )
{
Initialize( pSourceGrid, nrScales );
ArrayGrid<double>* pRecursiveInput = pSourceGrid;
for ( mCurrentScale = 0; mCurrentScale < mNrScales; mCurrentScale++)
{
int width = pRecursiveInput->GetWidth();
int height = pRecursiveInput->GetHeight();
int downScaledWidth = width / 2;
int downScaledHeight = height / 2;
bool needsInitialisation = true;
double initialValue = 0.0;
ArrayGrid<double>* pLLGrid = new ArrayGrid<double>( downScaledWidth, downScaledHeight, needsInitialisation, initialValue );
ArrayGrid<double>* pLHGrid = new ArrayGrid<double>( downScaledWidth, downScaledHeight, needsInitialisation, initialValue );
ArrayGrid<double>* pHLGrid = new ArrayGrid<double>( downScaledWidth, downScaledHeight, needsInitialisation, initialValue );
ArrayGrid<double>* pHHGrid = new ArrayGrid<double>( downScaledWidth, downScaledHeight, needsInitialisation, initialValue );
// to be sure that (x+1) and (y+1) won't exceed width and height
int limitWidth = (width / 2 ) * 2;
int limitHeight = (height / 2 ) * 2;
#ifdef DEBUG
cout << "Width = " << width << ", height = " << height << endl << flush;
cout << "limitWidth = " << limitWidth << ", limitHeight = " << limitHeight << endl << flush;
#endif
for (int y = 0; y < limitHeight; y+=2)
{
for (int x = 0; x < limitWidth; x+=2)
{
int halfX = x/2;
int halfY = y/2;
#ifdef DEBUG
//cout << "Width = " << width << ", height = " << height << endl << flush;
if ((x+1) > width) {cout << (x+1) << " goes out of bounds." << endl << flush;}
if ((y+1) > height) {cout << (y+1) << " goes out of bounds." << endl << flush;}
assert ((x+1) < width);
assert ((y+1) < height);
#endif
double x00 = pRecursiveInput->GetValue( x, y );
double x01 = pRecursiveInput->GetValue( x, y+1 );
double x10 = pRecursiveInput->GetValue( x+1, y );
double x11 = pRecursiveInput->GetValue( x+1, y+1 );
pLLGrid->SetValue( halfX, halfY, ( (x00 + x01 + x10 + x11) / 2.0) );
pLHGrid->SetValue( halfX, halfY, ( (x00 + x01 - x10 - x11) / 2.0) );
pHLGrid->SetValue( halfX, halfY, ( (x00 - x01 + x10 - x11) / 2.0) );
pHHGrid->SetValue( halfX, halfY, ( (x00 - x01 - x10 + x11) / 2.0) );
}
}
mpPyramid->GetRecursiveScale( mCurrentScale )->AddOrientedBand( pLHGrid ); // in on index 0
mpPyramid->GetRecursiveScale( mCurrentScale )->AddOrientedBand( pHLGrid ); // in on index 1
mpPyramid->GetRecursiveScale( mCurrentScale )->AddOrientedBand( pHHGrid ); // in on index 2
mpPyramid->SetLowpassResidual( pLLGrid );
pRecursiveInput = mpPyramid->GetLowpassResidual( );
}
return true;
}
image::ArrayGrid<double>* MedianFilter::RunHybridMedian( image::ArrayGrid<double>* pGridIn, int size)
{
int kernelSize = 4 * size + 1;
int medianPosition = (int)(kernelSize / 2);
int width = pGridIn->GetWidth();
int height = pGridIn->GetHeight();
double *pPlusShaped = new double [kernelSize];
double *pXShaped = new double [kernelSize];
double medianOfMedians[3], centralPixelValue;
ArrayGrid<double>* pGridOut = pGridIn->Clone();
for (int y = size; y < height - size; y++)
{
for (int x = size; x < width - size; x ++)
{
centralPixelValue = pGridIn->GetValue( x, y );
int index = 0;
for (int s = -size; s <= size; s++)
{
if (s != 0)
{
pPlusShaped[index] = pGridIn->GetValue( x + s, y );
index++;
}
}
for (int s = -size; s <= size; s++)
{
if (s != 0)
{
pPlusShaped[ index ] = pGridIn->GetValue( x, y + s );
index++;
}
}
pPlusShaped[ index ] = centralPixelValue ;
index = 0;
for (int s = -size; s <= size; s++)
{
if (s != 0)
{
pXShaped[ index ] = pGridIn->GetValue( x + s, y + s );
index++;
}
}
for (int s = -size; s <= size; s++)
{
if (s != 0)
{
pXShaped[ index ] = pGridIn->GetValue( x + s, y - s );
index ++;
}
}
pXShaped[ index ] = centralPixelValue;
qsort( pPlusShaped, kernelSize, sizeof(double), MathUtils::CompareDoubles );
qsort( pXShaped, kernelSize, sizeof(double), MathUtils::CompareDoubles );
medianOfMedians[ 0 ] = pPlusShaped[ medianPosition ];
medianOfMedians[ 1 ] = pXShaped[ medianPosition ];
medianOfMedians[ 2 ] = centralPixelValue;
qsort( medianOfMedians, 3, sizeof(double), MathUtils::CompareDoubles );
pGridOut->SetValue( x, y, medianOfMedians[1] );
}
}
delete []pPlusShaped;
delete []pXShaped;
return pGridOut;
}
ArrayGrid<bool>* StegerLineDetector::Run( ArrayGrid<double>* pGridIn, double sigmaSmooth, double lowerThreshold, double higherThreshold, bool isModeLight )
{
int width = pGridIn->GetWidth();
int height = pGridIn->GetHeight();
OrientationGrid* pOrientationGrid = new OrientationGrid(width, height); // NOT initialized at construction; values are set below
ArrayGrid<bool>* pLineGrid = new ArrayGrid<bool>(width, height); // NOT initialized at construction; values are set below
pLineGrid->SetGridValues( false );
ArrayGrid<double>* pGx = GaussConvolve::DerivativeConvolveFFT( pGridIn, sigmaSmooth, sigmaSmooth, GaussConvolve::DERIVATIVE_X );
ArrayGrid<double>* pGy = GaussConvolve::DerivativeConvolveFFT( pGridIn, sigmaSmooth, sigmaSmooth, GaussConvolve::DERIVATIVE_Y );
ArrayGrid<double>* pGxx = GaussConvolve::DerivativeConvolveFFT( pGridIn, sigmaSmooth, sigmaSmooth, GaussConvolve::DERIVATIVE_XX );
ArrayGrid<double>* pGyy = GaussConvolve::DerivativeConvolveFFT( pGridIn, sigmaSmooth, sigmaSmooth, GaussConvolve::DERIVATIVE_YY );
ArrayGrid<double>* pGxy = GaussConvolve::DerivativeConvolveFFT( pGridIn, sigmaSmooth, sigmaSmooth, GaussConvolve::DERIVATIVE_XY );
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double eigenValue1, eigenValue2, eigenValue;
common::Point<double> eigenVector1;
common::Point<double> eigenVector2;
EigenValueComputation( pGxx->GetValue(x, y), pGyy->GetValue(x, y), pGxy->GetValue(x, y),
eigenValue1, eigenValue2, eigenVector1, eigenVector2);
if (isModeLight == true)
{
eigenValue = -eigenValue1;
}
else
{
eigenValue = eigenValue1;
}
if (eigenValue > 0.0)
{
double n1 = eigenVector1.x;
double n2 = eigenVector1.y;
double a = pGxx->GetValue(x, y) * n1 * n1 + 2.0 * pGxy->GetValue(x, y) * n1 * n2 + pGyy->GetValue(x, y) * n2 * n2;
double b = pGx->GetValue(x, y) * n1 + pGy->GetValue(x, y) * n2;
double linearSolution;
if ( MathUtils::SolveLinearEquation( a, b, linearSolution ) == true )
{
double p1 = linearSolution * n1;
double p2 = linearSolution * n2;
if ((fabs (p1) <= EDGE_THRESHOLD) && (fabs (p2) <= EDGE_THRESHOLD))
{
int xx = (int)(x + p1 + 0.5);
int yy = (int)(y + p2 + 0.5);
if ( (xx >= 0) && (xx < width) && (yy >=0) && (yy < height))
{
if (eigenValue >= lowerThreshold)
{
if (eigenValue >= higherThreshold)
{
pLineGrid->SetValue(xx, yy, true);
}
}
else
{
pLineGrid->SetValue(xx, yy, false);
}
}
}
}
pOrientationGrid->SetAngle( x, y, MathUtils::ComputeArgument( eigenVector1.x, eigenVector1.y ) );
pOrientationGrid->SetMagnitude( x, y, eigenValue1);
}
}
}
//pOrientationGrid->ExportMagnitudeImage( string("StegerMagnitude.pgm") );
//pOrientationGrid->ExportOrientationImage( string("StegerOrientation.pgm"), -100000.0 );
delete pGx;
delete pGy;
delete pGxx;
delete pGyy;
delete pGxy;
delete pOrientationGrid;
return pLineGrid;
}
