In [2]:

    

import os
import cv2
import numpy as np

imagesList = list() # all images read from input folder (50)
INPUT_PATH = "./images/" # input folder
OUTPUT_PATH = "./results/" # output folder

# a function to display an image to screen and save it to a file
def showImageAndSaveToFile(img,output):
    cv2.namedWindow('image', cv2.WINDOW_NORMAL)
    cv2.imshow('image', img)
    cv2.waitKey(0) and cv2.destroyAllWindows()
    cv2.imwrite(output, img)

for fileName in os.listdir(INPUT_PATH): # read all images in input folder
    imagesList.append(cv2.imread(INPUT_PATH + fileName, cv2.IMREAD_GRAYSCALE))

xSize, ySize = imagesList[0].shape # get their shape

imgSum = np.zeros((xSize, ySize), dtype=np.uint16) # temporary matrix to store the sum of various uint8 matrixes (the images)
imgAvg = np.zeros((xSize, ySize), dtype=np.uint8) # matrix of the average of all the images read

for img in imagesList:
    imgSum = np.add(imgSum, img)

imgSum = np.divide(imgSum,len(imagesList)) # get average

imgAvg = imgSum.astype(np.uint8) # convert to uint8, expected by OpenCv
            
showImageAndSaveToFile(imgAvg, OUTPUT_PATH + "imgAvg.jpeg") # show the average image

imgBuff = np.zeros((xSize, ySize), dtype=np.float64) # temporary matrix to receive the computation of average noise image
imgNes = np.zeros((xSize, ySize), dtype=np.uint8) # matrix to output the computation done in the temporary matrix

for img in imagesList: #computing average noise
    imgBuff = np.add(imgBuff,np.subtract(imgAvg, img)**2)

imgBuff = np.square(np.divide(imgBuff, len(imagesList)))

imgNes = imgBuff.astype(np.uint8) # convert to uint8, expected by OpenCv
            
showImageAndSaveToFile(imgNes, OUTPUT_PATH + "imgNoiseAvg.jpeg")  # show the average noise image

avgNoise = (np.sum(imgNes))/(xSize*ySize) # average noise escalar
print(avgNoise)


    

    




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