Quantitatively check the quality of a compressed image by calculating the Structural Similarity Index (SSIM) and Mean Square Errors (MSE) between two images.

mse-ssim.py

#!/usr/bin/env python

from skimage.metrics import structural_similarity as ssim
import numpy as np
import cv2
import argparse

def options():
	parser = argparse.ArgumentParser(description="Read image metadata")
	parser.add_argument("-o", "--first", help="Input image file.", required=True)
	parser.add_argument("-c", "--second", help="Input image file.", required=True)
	args = parser.parse_args()
	return args

def mse(imageA, imageB):
	# the 'Mean Squared Error' between the two images is the sum of the squared difference between the two images
	mse_error = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2)
	mse_error /= float(imageA.shape[0] * imageA.shape[1])
	
	# return the MSE. The lower the error, the more "similar" the two images are.
	return mse_error

def compare(imageA, imageB):
	# Calculate the MSE and SSIM
	m = mse(imageA, imageB)
	s = ssim(imageA, imageB)

	# Return the SSIM. The higher the value, the more "similar" the two images are.
	return s

def main(): 

	# Get options
	args = options()

	# Import images
	image1 = cv2.imread(args.first)
	image2 = cv2.imread(args.second, 1)

	# Convert the images to grayscale
	gray1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
	gray2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)

	# Check for same size and ratio and report accordingly
	ho, wo, _ = image1.shape
	hc, wc, _ = image2.shape
	ratio_orig = ho/wo
	ratio_comp = hc/wc
	dim = (wc, hc)

	if round(ratio_orig, 2) != round(ratio_comp, 2):
		print("\nImages not of the same dimension. Check input.")
		exit()

	# Resize first image if the second image is smaller
	elif ho > hc and wo > wc:
		print("\nResizing original image for analysis...")
		gray1 = cv2.resize(gray1, dim)

	elif ho < hc and wo < wc:
		print("\nCompressed image has a larger dimension than the original. Check input.")
		exit()

	if round(ratio_orig, 2) == round(ratio_comp, 2):

		mse_value = mse(gray1, gray2)
		ssim_value = compare(gray1, gray2)
		print("MSE:", mse_value)
		print("SSIM:", ssim_value)

if __name__ == '__main__':
	main()