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clahe_adaptive_he.py
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clahe_adaptive_he.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Feb 23 12:55:43 2021
@author: kaust
"""
import cv2
import numpy as np
# Reading the image from the present directory
image = cv2.imread("img_6_1.jpg")
# Resizing the image for compatibility
image = cv2.resize(image, (500, 600))
# The initial processing of the image
# image = cv2.medianBlur(image, 3)
image_bw = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# The declaration of CLAHE
# clipLimit -> Threshold for contrast limiting
clahe = cv2.createCLAHE(clipLimit = 5)
final_img1 = clahe.apply(image_bw) + 30
# Ordinary thresholding the same image
#_, ordinary_img = cv2.threshold(image_bw, 155, 255, cv2.THRESH_BINARY)
# Showing all the three images
#cv2.imshow("ordinary threshold", ordinary_img)
cv2.imshow("CLAHE image", final_img1)
cv2.imwrite("clahe_1.jpg", final_img1)
image2 = cv2.imread("img_6_2.jpg")
# Resizing the image for compatibility
image2 = cv2.resize(image2, (500, 600))
# The initial processing of the image
# image = cv2.medianBlur(image, 3)
image_bw2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
# The declaration of CLAHE
# clipLimit -> Threshold for contrast limiting
clahe2 = cv2.createCLAHE(clipLimit = 5)
final_img2 = clahe2.apply(image_bw2) + 30
cv2.imshow("CLAHE image2", final_img2)
cv2.imwrite("clahe_2.jpg", final_img2)
original_img_L1 = cv2.norm(image - image2, cv2.NORM_L1)
print("L1 distance of before normalization: ",original_img_L1)
original_img_L2 = cv2.norm(image - image2, cv2.NORM_L2)
print("L2 distance of before normalization: ",original_img_L2)
normalized_img_L1 = cv2.norm(final_img1 - final_img2, cv2.NORM_L1)
print("L1 distance of after normalization: ",normalized_img_L1)
normalized_img_L2 = cv2.norm(final_img1 - final_img2, cv2.NORM_L2)
print("L1 distance of after normalization: ",normalized_img_L2)
cv2.waitKey(0)
cv2.destroyAllWindows()