def test_masked_registration_random_masks_non_equal_sizes():
"""masked_register_translation should be able to register
translations between images that are not the same size even
with random masks."""
# See random number generator for reproducible results
np.random.seed(23)
reference_image = cp.asarray(camera())
shift = (-7, 12)
shifted = cp.real(
fft.ifft2(fourier_shift(fft.fft2(reference_image), shift)))
# Crop the shifted image
shifted = shifted[64:-64, 64:-64]
# Random masks with 75% of pixels being valid
ref_mask = np.random.choice([True, False],
reference_image.shape,
p=[3 / 4, 1 / 4])
shifted_mask = np.random.choice([True, False],
shifted.shape,
p=[3 / 4, 1 / 4])
reference_image = cp.asarray(reference_image)
shifted = cp.asarray(shifted)
measured_shift = masked_register_translation(
reference_image,
shifted,
cp.ones(ref_mask.shape, dtype=ref_mask.dtype),
cp.ones(shifted_mask.shape, dtype=shifted_mask.dtype),
)
cp.testing.assert_array_equal(measured_shift, -cp.asarray(shift))
def test_masked_registration_vs_phase_cross_correlation():
"""masked_register_translation should give the same results as
phase_cross_correlation in the case of trivial masks."""
reference_image = cp.asarray(camera())
shift = (-7, 12)
shifted = cp.real(
fft.ifft2(fourier_shift(fft.fft2(reference_image), shift)))
trivial_mask = cp.ones_like(reference_image)
nonmasked_result, *_ = phase_cross_correlation(reference_image, shifted)
masked_result = masked_register_translation(reference_image,
shifted,
trivial_mask,
overlap_ratio=0.1)
cp.testing.assert_array_equal(nonmasked_result, masked_result)
def test_masked_registration_random_masks():
"""masked_register_translation should be able to register translations
between images even with random masks."""
# See random number generator for reproducible results
np.random.seed(23)
reference_image = cp.asarray(camera())
shift = (-7, 12)
shifted = np.real(
fft.ifft2(fourier_shift(fft.fft2(reference_image), shift)))
# Random masks with 75% of pixels being valid
ref_mask = np.random.choice([True, False],
reference_image.shape,
p=[3 / 4, 1 / 4])
shifted_mask = np.random.choice([True, False],
shifted.shape,
p=[3 / 4, 1 / 4])
ref_mask = cp.asarray(ref_mask)
shifted_mask = cp.asarray(shifted_mask)
measured_shift = masked_register_translation(reference_image, shifted,
ref_mask, shifted_mask)
cp.testing.assert_array_equal(measured_shift, -cp.asarray(shift))