lady.py

# Import Library

import matplotlib
import cv2
from fungsi import noisy
from fungsi import ftAritmatik
from fungsi import ftMedian
from fungsi import ftAlphaTrimmedMean
from fungsi import mse

# https://askubuntu.com/questions/764895/segmentation-fault-core-dumped-using-matplotlib-on-ubuntu-mate-16-04
# print(plt.get_backend())
matplotlib.use("GTK3Agg") 

# print(pyplot)

import matplotlib.pyplot as plt
# plt=matplotlib.pyplot


# Open Image -> Grayscale
imgAsli = cv2.imread('img/lady.jpeg', cv2.IMREAD_GRAYSCALE)




# Add Noise salt and paper
imgNoisy=noisy("s&p",imgAsli)

# print(imgAsli)
# 1. Show image
cv2.imshow('Gambar Noisy',imgNoisy)

print("Mean Squared Error (Noisy) : ",mse(imgAsli,imgNoisy))
# 2. Show histogram
# histr = cv2.calcHist([imgNoisy],[0],None,[256],[0,256])
# plt.plot(histr) 
# plt.title("Gambar Noisy") 
# plt.ylabel("frequency")
# plt.xlabel("range")
# plt.show()




# A. Filter Rata rata Aritmatik
# 1. Show image
A=ftAritmatik(imgNoisy)
cv2.imshow('Filter Rata rata Aritmatik',A)

# print("Mean Squared Error (Filter Rata rata Aritmetik) : ",mse(imgAsli,A))

# 2. Show histogram
# histr1 = cv2.calcHist([A],[0],None,[256],[0,256])
# plt.plot(histr1)
# plt.title("Filter Rata rata Aritmatik") 
# plt.ylabel("frequency")
# plt.xlabel("range")
# plt.show() 






# Filter Median
# 1. Show image
B=ftMedian(imgNoisy)
cv2.imshow('Filter Median',B)

print("Mean Squared Error (Filter Median) : ",mse(imgAsli,B))

# 2. Show histogram
# histr2 = cv2.calcHist([B],[0],None,[256],[0,256])
# plt.plot(histr2)
# plt.title("Filter Median") 
# plt.ylabel("frequency")
# plt.xlabel("range")
# plt.show() 




# Filter Alpha-Trimmed Mean
# 1. Show image
C=ftAlphaTrimmedMean(imgNoisy)
cv2.imshow('Filter Alpha-Trimmed Mean',C)

print("Mean Squared Error (Filter Alpha Trimmed Mean) : ",mse(imgAsli,C))
# 2. Show histogram
# histr2 = cv2.calcHist([C],[0],None,[256],[0,256])
# plt.plot(histr2)
# plt.title("Filter Alpha-Trimmed Mean") 
# plt.ylabel("frequency")
# plt.xlabel("range")
# plt.show()



# Wait until close image close
cv2.waitKey(20000)