public void FromGrayImage(GrayScaleImage gimage)
{
ImageMatrix[0] = new DenseMatrix(gimage.RowCount, gimage.ColumnCount);
ImageMatrix[1] = new DenseMatrix(gimage.RowCount, gimage.ColumnCount);
ImageMatrix[2] = new DenseMatrix(gimage.RowCount, gimage.ColumnCount);
int x, y;
for(x = 0; x < ColumnCount; ++x)
{
for(y = 0; y < RowCount; ++y)
{
this[y, x, 0] = gimage[y, x];
this[y, x, 1] = gimage[y, x];
this[y, x, 2] = gimage[y, x];
}
}
}
public void StretchHistogram(GrayScaleImage image)
{
HistogramOperations.StretchHistogram(image);
}
public GrayImageDebugView(GrayScaleImage img)
{
_image = img;
}
public void SaturateRatioHistogram(GrayScaleImage image)
{
HistogramOperations.SaturateRatioHistogram(image, SaturateRatioLow, SaturateRatioHigh);
}
public void EqualizeHistogram(GrayScaleImage image)
{
HistogramOperations.EqualizeHistogram(image);
}
public override bool Detect()
{
int ymax = Image.SizeY - _borderSize;
int xmax = Image.SizeX - _borderSize;
int x, y, dx, dy;
double[,] usan = new double[7, 7];
FeatureMap = new GrayScaleImage()
{
ImageMatrix = new DenseMatrix(Image.SizeY, Image.SizeX)
};
double response = 0.0f;
// Look-up table for current threshold for fast assimiliance computing
double[] assimilianceLUT = new double[512];
for(int di = 0; di < 511; di++)
{
assimilianceLUT[di] = (double)Math.Exp(
-Math.Pow( (((double)(di-255))/255.0f) / _t_intensity, 6) );
}
int dymax;
// For each point in image
for (x = _borderSize; x < xmax; ++x)
{
for (y = _borderSize; y < ymax; ++y)
{
response = 0.0f;
// For each point in usan mask
for(dx = -3; dx <= 3; dx++ )
{
dymax = _ybounds[dx + 3];
for (dy = -_ybounds[dx+3]; dy <= dymax; ++dy)
{
// Find its usan assimiliance coeff
// usan[dy + 3, dx + 3] = (double)Math.Exp(
// -(double)Math.Pow(((Image[y,x] - Image[y+dy,x+dx]) / _t_intensity), 6) );
// usan[dy + 3, dx + 3] = assimilianceLUT[(int)(Math.Abs(Image[y, x] - Image[y + dy, x + dx]) * 255)];
response += assimilianceLUT[(int)((Image[y, x] - Image[y + dy, x + dx]) * 255) + 256];
}
}
// Response <= threshold -> no feature
FeatureMap[y, x] = (double)Math.Max(0.0, -_t_isFeature + response);
}
}
if (_nonMaxSup)
{
Matrix<double> resp = FeatureMap.ImageMatrix.Clone();
//Non max suppresion
for (x = _borderSize; x < xmax; ++x)
{
for (y = _borderSize; y < ymax; ++y)
{
if (FeatureMap[y, x] > 0.0f)
if(!IsMaximum(resp, y, x, 2))
{
FeatureMap[y, x] = 0.0f;
}
}
}
}
return true;
}
public override void Detect()
{
Terminate = false;
int ymax = Image.RowCount - _borderSize;
int xmax = Image.ColumnCount - _borderSize;
int x, y, dx, dy;
double[,] usan = new double[7, 7];
FeatureMap = new GrayScaleImage()
{
ImageMatrix = new DenseMatrix(Image.RowCount, Image.ColumnCount)
};
FeaturePoints = new List<IntVector2>();
double response = 0.0f;
// Look-up table for current threshold for fast assimiliance computing
double[] assimilianceLUT = new double[512];
for(int di = 0; di < 511; di++)
{
assimilianceLUT[di] = Math.Exp(-Math.Pow(
((di - 255.0) / 255.0) / _t_intensity, 6));
}
int dymax;
// For each point in image
for(x = _borderSize; x < xmax; ++x)
{
CurrentPixel.X = x;
for(y = _borderSize; y < ymax; ++y)
{
if(Terminate) return;
CurrentPixel.Y = y;
if(Image.HaveValueAt(y, x))
{
response = 0.0;
// For each point in usan mask
for(dx = -3; dx <= 3; dx++)
{
dymax = _ybounds[dx + 3];
for(dy = -_ybounds[dx + 3]; dy <= dymax; ++dy)
{
// Find its usan assimiliance coeff
// usan[dy + 3, dx + 3] = (double)Math.Exp(
// -(double)Math.Pow(((Image[y,x] - Image[y+dy,x+dx]) / _t_intensity), 6) );
// usan[dy + 3, dx + 3] = assimilianceLUT[(int)(Math.Abs(Image[y, x] - Image[y + dy, x + dx]) * 255)];
response += assimilianceLUT[(int)((Image[y, x] - Image[y + dy, x + dx]) * 255) + 256];
}
}
// Response >= threshold -> no feature
FeatureMap[y, x] = Math.Max(0.0, _t_isFeature - response);
if(!_nonMaxSup)
FeaturePoints.Add(new IntVector2(x, y));
}
}
}
if(_nonMaxSup)
{
Matrix<double> resp = FeatureMap.ImageMatrix.Clone();
//Non max suppresion
for(x = _borderSize; x < xmax; ++x)
{
CurrentPixel.X = x;
for(y = _borderSize; y < ymax; ++y)
{
if(Terminate) return;
CurrentPixel.Y = y;
if(FeatureMap[y, x] > 0.0f)
{
//if(!IsMaximum(resp, y, x, 2))
//{
// FeatureMap[y, x] = 0.0f;
//}
//else
// FeaturePoints.Add(new IntVector2(x, y));
FloodFindMaximum(y, x);
}
}
}
for(x = 0; x < Image.ColumnCount; ++x)
{
for(y = 0; y < Image.RowCount; ++y)
{
if(FeatureMap[y, x] > 0.0)
{
FeaturePoints.Add(new IntVector2(x, y));
}
}
}
}
// Scale map so that max feature is 1
FeatureMap.ImageMatrix.MultiplyThis(1.0 / FeatureMap.ImageMatrix.AbsoulteMaximum().Item3);
return;
}
private void _butSegment_Click(object sender, RoutedEventArgs e)
{
if(_imageControl.ImageSource != null)
{
ColorImage img = new ColorImage();
img.FromBitmapSource(_imageControl.ImageSource);
var window = new ParametrizedProcessorsSelectionWindow();
window.AddProcessorFamily("Segmentation");
window.AddToFamily("Segmentation", new MeanShiftSegmentation());
window.ShowDialog();
if(window.Accepted)
{
ImageSegmentation segmentation = (ImageSegmentation)window.GetSelectedProcessor("Segmentation");
GrayScaleImage imgGray = new GrayScaleImage();
imgGray.FromColorImage(img);
//segmentation.SegmentColor(img);
segmentation.SegmentGray(imgGray.ImageMatrix);
//var segments = segmentation.Segments_Color;
var segments = segmentation.Segments;
int[,] indices = segmentation.SegmentAssignments;
ColorImage imgFinal = new ColorImage();
imgFinal.ImageMatrix[0] = new DenseMatrix(img.RowCount, img.ColumnCount);
imgFinal.ImageMatrix[1] = new DenseMatrix(img.RowCount, img.ColumnCount);
imgFinal.ImageMatrix[2] = new DenseMatrix(img.RowCount, img.ColumnCount);
for(int r = 0; r < img.RowCount; ++r)
{
for(int c = 0; c < img.ColumnCount; ++c)
{
imgFinal[r, c, RGBChannel.Red] = ((ImageSegmentation.Segment_Gray)segments[indices[r, c]]).Value;
imgFinal[r, c, RGBChannel.Green] = ((ImageSegmentation.Segment_Gray)segments[indices[r, c]]).Value;
imgFinal[r, c, RGBChannel.Blue] = ((ImageSegmentation.Segment_Gray)segments[indices[r, c]]).Value;
//imgFinal[r, c, RGBChannel.Red] = segments[indices[r, c]].Red;
// imgFinal[r, c, RGBChannel.Green] = segments[indices[r, c]].Green;
//imgFinal[r, c, RGBChannel.Blue] = segments[indices[r, c]].Blue;
}
}
_imageControl.ImageSource = imgFinal.ToBitmapSource();
}
}
}