/**
* Searches the pyramid layers up and down to see if the found 2D features are also scale space
* maximums.
*/
protected void findLocalScaleSpaceMax(GaussianScaleSpace<T, D> ss, int layerID) {
int index0 = spaceIndex;
int index1 = (spaceIndex + 1) % 3;
int index2 = (spaceIndex + 2) % 3;
List<Point2D_I16> candidates = maximums[index1];
T image0 = localSpace[index0];
T image1 = localSpace[index1];
T image2 = localSpace[index2];
float scale0 = (float) ss.getScale(layerID - 1);
float scale1 = (float) ss.getScale(layerID);
float scale2 = (float) ss.getScale(layerID + 1);
// For laplacian its t^(2*gamma) where gamma = 3/4
float ss0 = (float) Math.pow(scale0, 2.0 * 0.75);
float ss1 = (float) Math.pow(scale1, 2.0 * 0.75);
float ss2 = (float) Math.pow(scale2, 2.0 * 0.75);
for (Point2D_I16 c : candidates) {
sparseLaplace.setImage(image1);
float val = ss1 * (float) Math.abs(sparseLaplace.compute(c.x, c.y));
if (checkMax(image0, ss0, val, c.x, c.y) && checkMax(image2, ss2, val, c.x, c.y)) {
// put features into the scale of the upper image
foundPoints.add(new ScalePoint(c.x, c.y, scale1));
}
}
}
private boolean checkMax(T image, float scoreAdjust, float bestScore, int c_x, int c_y) {
sparseLaplace.setImage(image);
boolean isMax = true;
beginLoop:
for (int i = c_y - 1; i <= c_y + 1; i++) {
for (int j = c_x - 1; j <= c_x + 1; j++) {
if (scoreAdjust * Math.abs(sparseLaplace.compute(j, i)) >= bestScore) {
isMax = false;
break beginLoop;
}
}
}
return isMax;
}
