#...........................Additional notes............................
'''In addition to cv2.GaussianBlur() filter, other commonly used filters
are: Average blur, cv2.blur(); Median blur, cv2.medianBlur(); and
and Bilateral filter, cv2.bilateralFilter. For example, Bilateral filter
can be used to filter high frequecy components while maintaining the
edges of the image, this is the strength of this filter compared to others.
The example below implements the Bilateral filter:'''
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("myimage.jpg")
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
diameter = 30# diameter of the pixels included in the neighborhood.
sigmaColor = 20 # color standard deviation in the neighborhood.
sigmaSpace = 20 # space standard deviation in the neighborhood
blurred = cv2.bilateralFilter(img, diameter, sigmaColor, sigmaSpace)
plt.imshow(threshdimage, cmap = 'gray', interpolation = 'bicubic')# plot
plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axis
plt.show()