diff --git a/datasets/raise/fft/get_ft_prnu.py b/datasets/raise/fft/get_ft_prnu.py
new file mode 100644
index 0000000..cb157a1
--- /dev/null
+++ b/datasets/raise/fft/get_ft_prnu.py
@@ -0,0 +1,27 @@
+#!/usr/bin/python3
+
+import cv2
+import numpy as np
+
+# now we will be loading the image and converting it to grayscale
+image = cv2.imread(r'-002.ppm')
+
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+# Compute the discrete Fourier Transform of the image
+fourier = cv2.dft(np.float32(gray), flags=cv2.DFT_COMPLEX_OUTPUT)
+
+# Shift the zero-frequency component to the center of the spectrum
+fourier_shift = np.fft.fftshift(fourier)
+
+# calculate the magnitude of the Fourier Transform
+magnitude = 20*np.log(cv2.magnitude(fourier_shift[:,:,0],fourier_shift[:,:,1]))
+
+# Scale the magnitude for display
+magnitude = cv2.normalize(magnitude, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8UC1)
+
+# Display the magnitude of the Fourier Transform
+cv2.imshow('Fourier Transform', magnitude)
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+