diff --git a/102-What is Unsharp Mask.py b/102-What is Unsharp Mask.py
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+#!/usr/bin/env python
+__author__ = "Sreenivas Bhattiprolu"
+__license__ = "Feel free to copy, I appreciate if you acknowledge Python for Microscopists"
+
+# https://youtu.be/u_4d51bOsVs
+
+"""
+Unsharp mask enhances edges by subtracting an unsharp (smoothed) version of the image from the original.
+Effectively making the filter a high pass filter. 
+
+enhanced image = original + amount * (original - blurred)
+
+Amount of sharpening can be controlled via scaling factor, a multiplication factor
+for the sharpened signal. 
+
+skimage uses Gaussian smoothing for image blurring therefore the radius parameter 
+in the unsharp masking filter refers to the sigma parameter of the gaussian filter.
+#This code shows that unsharp is nothing but original + amount *(original-blurred)
+from skimage import io, img_as_float
+from skimage.filters import unsharp_mask
+from skimage.filters import gaussian
+
+img = img_as_float(io.imread("images/einstein_blurred.jpg", as_gray=True))
+
+gaussian_img = gaussian(img, sigma=1, mode='constant', cval=0.0)
+
+img2 = (img - gaussian_img)*1.
+
+img3 = img + img2
+
+from matplotlib import pyplot as plt
+plt.imshow(img3, cmap="gray")
+
+"""
+
+from skimage import io
+from skimage.filters import unsharp_mask
+
+img = io.imread("images/einstein_blurred.jpg")
+
+#sharpened = unsharp_mask(image0, radius=1.0, amount=1.0)
+unsharped_img = unsharp_mask(img, radius=3, amount=1)
+
+
+import matplotlib.pyplot as plt
+fig = plt.figure(figsize=(12, 12))
+ax1 = fig.add_subplot(2,2,1)
+ax1.imshow(img, cmap='gray')
+ax1.title.set_text('Input Image')
+ax2 = fig.add_subplot(2,2,2)
+ax2.imshow(unsharped_img, cmap='gray')
+ax2.title.set_text('Unsharped Image')
+
+plt.show()
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