HW9-Generate Gaussian Nosie

Author: NUZEROVI

05.Generate Noise/Add_Gaussian_Noise.py

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+# HW9-method1 (Generation of zero mean Gaussian noise)
+
+from PIL import Image
+import numpy as np
+import matplotlib.pyplot as plt
+
+# 1. Create an image g and the same gray values of 100
+g = Image.open("g.png").convert("L")
+for i in range(g.size[0]):
+    for j in range(g.size[1]):
+        g.putpixel((i, j), 100)
+
+g.save("g.png")
+g.show()
+
+# Save image g histogram
+a = np.array(g)
+plt.hist(a.ravel(), bins=256)
+plt.ylabel('Number of pixels')
+plt.xlabel('Gray Scale')
+plt.savefig('g_histogram.png')
+plt.show()
+
+# 2. Generate Gaussian noise n and Show noisy image f
+# Calculate Gaussian noise with menu=0 and variance=15
+menu = 0
+variance = 15
+noise = np.random.normal(menu, variance, g.size)
+# Add the noise to the image g
+f_array_noise = np.add(np.array(g), noise) # f = g + noise
+f = Image.fromarray(f_array_noise)
+# Show the noisy image f
+f.show()
+
+# 3. Save and display noisy image f histogram
+a = np.array(f)
+plt.hist(a.ravel(), bins=256)
+plt.ylabel('Number of pixels')
+plt.xlabel('Gray Scale')
+plt.savefig('f_histogram.png')
+plt.show()