To obtain a histogram for finding the frequency of pixels in an Image with pixel values ranging from 0 to 255. Also write the code using OpenCV to perform histogram equalization.
Anaconda - Python 3.7
Import the necessary libraries and read two images, Color image and Gray Scale image.
Calculate the Histogram of Gray scale image and each channel of the color image.
Display the histograms with their respective images.
Equalize the grayscale image.
Display the grayscale image.
Developed By:DurgaDevi P
Register Number:212220230015
# Write your code to find the histogram of gray scale image and color image channels.
import cv2
import matplotlib.pyplot as plt
Gray_image=cv2.imread('parrot.png')
plt.imshow(Gray_image)
plt.show()
hist=cv2.calcHist([Gray_image],[0],None,[256],[0,256])
plt.figure()
plt.title("Histogram")
plt.xlabel('grayscale value')
plt.ylabel('pixel count')
plt.stem(hist)
plt.show()
# Display the histogram of gray scale image and any one channel histogram from color image
import cv2
import matplotlib.pyplot as plt
Color_image=cv2.imread('dog.jpg')
plt.imshow(Color_image)
plt.show()
hist1=cv2.calcHist([Color_image],[1],None,[256],[0,256])
plt.figure()
plt.title("Histogram")
plt.xlabel('Intensity value')
plt.ylabel('pixel count')
plt.stem(hist1)
plt.show()
# Write the code to perform histogram equalization of the image.
import cv2
Gray_image=cv2.imread('parrot.png',0)
equ=cv2.equalizeHist(Gray_image)
cv2.imshow('Gray Image',Gray_image)
cv2.imshow('Equalized Image',equ)
cv2.waitKey(0)
cv2.destroyAllWindows()
Thus the histogram for finding the frequency of pixels in an image with pixel values ranging from 0 to 255 is obtained. Also,histogram equalization is done for the gray scale image using OpenCV.