text: # Importing necessary libraries and dependencies
  import numpy as np
  import cv2
  from matplotlib import pyplot as plt
  from PIL import Image, ImageFilter
  
  # Read image files
  noise = cv2.imread('../images/noise.jpg')
  noise1 = cv2.imread('../images/noise1.jpg')
  
  ###-------------------------------###
  ### MEDIAN FILTER FOR NOISE IMAGE ###
  ###-------------------------------###
  
  # In RGB information concerning color and luminance can not be separated. HSV is used to separate image luminance from color information and hence is required.
  noise = cv2.cvtColor(noise, cv2.COLOR_BGR2HSV)
  noise1 = cv2.cvtColor(noise1, cv2.COLOR_BGR2HSV)
  
  figure_size = 5
  median_noise = cv2.medianBlur(noise, figure_size)
  plt.figure(figsize=(9,7))
  plt.subplot(221)
  plt.imshow(cv2.cvtColor(noise, cv2.COLOR_HSV2RGB))
  plt.title('Original picture of Asian man')
  plt.xticks([])
  plt.yticks([])
  plt.subplot(222)
  plt.imshow(cv2.cvtColor(median_noise, cv2.COLOR_HSV2RGB))
  plt.title('Median Filter (Size 5 for best result)')
  plt.xticks([])
  plt.yticks([])
  
  ###--------------------------------###
  ### MEDIAN FILTER FOR NOISE1 IMAGE ###
  ###--------------------------------###
  
  figure_size = 3
  median_noise1 = cv2.medianBlur(noise1, figure_size)
  plt.subplot(223)
  plt.imshow(cv2.cvtColor(noise1, cv2.COLOR_HSV2RGB))
  plt.title('Original picture of tiger')
  plt.xticks([])
  plt.yticks([])
  plt.subplot(224)
  plt.imshow(cv2.cvtColor(median_noise1, cv2.COLOR_HSV2RGB))
  plt.title('Median Filter (Size 3 for best result)')
  plt.xticks([])
  plt.yticks([])
  plt.show()