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Updating Fourier similarity to an RMSE of the power spectrum between two images #17

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Updating Fourier similarity to an RMSE of the power spectrum between two images #17

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961b416
Updated hologram example
jsschreck Oct 30, 2023
221bfb7
Updated Fourier sim to RMSE
jsschreck Dec 11, 2023
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77 changes: 56 additions & 21 deletions notebooks/hologram_propagation.ipynb
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4 changes: 2 additions & 2 deletions src/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
grad_total_variation
)
from .fourier import (
fourier_image_similarity,
fourier_rmse,
fourier_total_variation
)
from .wavelet import (
Expand All @@ -37,10 +37,10 @@
"grad-ds": gradient_difference_similarity,
"grad-rmse": gradient_rmse,
"laplace-rmse": laplacian_rmse,
"fourier-rmse": fourier_rmse,
"hist-int": histogram_intersection,
#"gpd": gradient_profile_difference,
"hog-pearson": hog_pearson,
"fourier-similarity": fourier_image_similarity,
"wavelet-similarity": wavelet_image_similarity,
"tv": total_variation,
"grad-tv": grad_total_variation,
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17 changes: 6 additions & 11 deletions src/fourier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,19 +7,14 @@ def compute_power_spectrum(image):
power_spectrum = np.abs(f_transform) ** 2
return power_spectrum

def fourier_image_similarity(image1, image2):
def fourier_rmse(image1, image2):
# Compute power spectra of both images
power_spectrum1 = compute_power_spectrum(image1)
power_spectrum2 = compute_power_spectrum(image2)

# Compute the normalized cross-correlation between power spectra
cross_correlation = np.real(np.fft.ifft2(np.fft.fft2(power_spectrum1) * np.conj(np.fft.fft2(power_spectrum2))))
cross_correlation /= np.max(cross_correlation)

# The maximum value of the cross-correlation indicates similarity
similarity_score = np.max(cross_correlation)

return similarity_score
# Compute the mean squared error between power spectra
mse = np.mean((power_spectrum1-power_spectrum2)**2)
return np.sqrt(mse)

def fourier_total_variation(image):
f_transform = np.fft.fft2(image)
Expand All @@ -32,5 +27,5 @@ def fourier_total_variation(image):
image1 = camera()
image2 = camera()

similarity_score = fourier_image_similarity(image1, image2)
print("Similarity Score:", similarity_score)
fourier_mse = fourier_mse(image1, image2)
print("Fourier power spectrum MSE:", fourier_mse)