@Test
public void computeScaleSigma() {
SiftImageScaleSpace alg = new SiftImageScaleSpace(1.6f, 5, 2, false);
assertEquals(1.6, alg.computeScaleSigma(0, 0), 1e-4);
assertEquals(3.2, alg.computeScaleSigma(0, 1), 1e-4);
assertEquals(4.8, alg.computeScaleSigma(0, 2), 1e-4);
// compute total gaussian blur from previous set taken at level 2
double prev = 2 * 1.6;
// Each level still has 1.6, but at 1/2 the resolution
double next1 = Math.sqrt(prev * prev + 4 * 1.6 * 1.6);
double next2 = Math.sqrt(prev * prev + 4 * 3.2 * 3.2);
assertEquals(next1, alg.computeScaleSigma(1, 0), 1e-4);
assertEquals(next2, alg.computeScaleSigma(1, 1), 1e-4);
}
@Test
public void scaleToImageIndex() {
SiftImageScaleSpace alg = new SiftImageScaleSpace(1.6f, 5, 2, false);
// try easy cases exactly on the nominal sigma
assertEquals(0, alg.scaleToImageIndex(alg.computeScaleSigma(0, 0)));
assertEquals(1, alg.scaleToImageIndex(alg.computeScaleSigma(0, 1)));
assertEquals(2, alg.scaleToImageIndex(alg.computeScaleSigma(0, 2)));
assertEquals(5, alg.scaleToImageIndex(alg.computeScaleSigma(1, 0)));
assertEquals(6, alg.scaleToImageIndex(alg.computeScaleSigma(1, 1)));
assertEquals(9, alg.scaleToImageIndex(alg.computeScaleSigma(1, 4)));
// try cases slightly off from nominal
assertEquals(0, alg.scaleToImageIndex(alg.computeScaleSigma(0, 0) - 0.01));
assertEquals(0, alg.scaleToImageIndex(alg.computeScaleSigma(0, 0) + 0.01));
assertEquals(9, alg.scaleToImageIndex(alg.computeScaleSigma(1, 4) - 0.01));
assertEquals(9, alg.scaleToImageIndex(alg.computeScaleSigma(1, 4) + 0.01));
// try the extreme ends, which should round in the wrong direction
assertEquals(0, alg.scaleToImageIndex(0));
assertEquals(9, alg.scaleToImageIndex(alg.computeScaleSigma(1, 4) + 1.6 * 2));
}
