public void process(final BufferedImage input) {
setInputImage(input);
this.input = input;
workImage = ConvertBufferedImage.convertFromSingle(input, null, imageType);
scaledIntensity = new ImageFloat32(workImage.width, workImage.height);
pyramid.setImage(workImage);
SwingUtilities.invokeLater(
new Runnable() {
public void run() {
setPreferredSize(new Dimension(input.getWidth(), input.getHeight()));
processedImage = true;
}
});
doRefreshAll();
}
@Override
public void setActiveAlgorithm(int indexFamily, String name, Object cookie) {
if (input == null) {
return;
}
GeneralFeatureIntensity<T, D> intensity = (GeneralFeatureIntensity<T, D>) cookie;
gui.reset();
BufferedImage b = VisualizeImageData.grayMagnitude(workImage, null, 255);
gui.addImage(b, "Gray Image");
final ProgressMonitor progressMonitor =
new ProgressMonitor(
this, "Computing Scale Space Pyramid Response", "", 0, pyramid.getNumLayers());
for (int i = 0; i < pyramid.getNumLayers() && !progressMonitor.isCanceled(); i++) {
double scale = pyramid.getScale(i);
T scaledImage = pyramid.getLayer(i);
anyDerivative.setInput(scaledImage);
D derivX = anyDerivative.getDerivative(true);
D derivY = anyDerivative.getDerivative(false);
D derivXX = anyDerivative.getDerivative(true, true);
D derivYY = anyDerivative.getDerivative(false, false);
D derivXY = anyDerivative.getDerivative(true, false);
intensity.process(scaledImage, derivX, derivY, derivXX, derivYY, derivXY);
ImageFloat32 featureImg = intensity.getIntensity();
// scale it up to full resolution
DistortImageOps.scale(featureImg, scaledIntensity, TypeInterpolate.NEAREST_NEIGHBOR);
// visualize the rescaled intensity
b = VisualizeImageData.colorizeSign(scaledIntensity, null, PixelMath.maxAbs(scaledIntensity));
gui.addImage(b, String.format("Scale %6.2f", scale));
final int progressStatus = i + 1;
SwingUtilities.invokeLater(
new Runnable() {
public void run() {
progressMonitor.setProgress(progressStatus);
}
});
}
gui.requestFocusInWindow();
}