09-rescaling-pixel-intensities.py

'''
Rescaling pixel intensities

Sometimes, low contrast images can be improved by rescaling their intensities. For instance, this image of Hawkes Bay, New Zealand (originally by Phillip Capper, modified by User:Konstable, via Wikimedia Commons, CC BY 2.0) has no pixel values near 0 or near 255 (the limits of valid intensities).

For this exercise, you will do a simple rescaling (remember, an image is NumPy array) to translate and stretch the pixel intensities so that the intensities of the new image fill the range from 0 to 255.

INSTRUCTIONS
100XP
Use the methods .min() and .max() to save the minimum and maximum values from the array image as pmin and pmax respectively.
Create a new 2-D array rescaled_image using 256*(image-pmin)/(pmax-pmin)
Plot the original array image in the top subplot of a 2×1
2
×
1
grid.
Plot the new array rescaled_image in the bottom subplot of a 2×1
2
×
1
 grid.
 '''
 # Load the image into an array: image
image = plt.imread('640px-Unequalized_Hawkes_Bay_NZ.jpg')

# Extract minimum and maximum values from the image: pmin, pmax
pmin, pmax = image.min(), image.max()
print("The smallest & largest pixel intensities are %d & %d." % (pmin, pmax))

# Rescale the pixels: rescaled_image
rescaled_image = 256*(image - pmin) / (pmax - pmin)
print("The rescaled smallest & largest pixel intensities are %.1f & %.1f." % 
      (rescaled_image.min(), rescaled_image.max()))

# Display the original image in the top subplot
plt.subplot(2,1,1)
plt.title('original image')
plt.axis('off')
plt.imshow(image)

# Display the rescaled image in the bottom subplot
plt.subplot(2,1,2)
plt.title('rescaled image')
plt.axis('off')
plt.imshow(rescaled_image)

plt.show()