Histogram and Histogram Equalization of an image:

Aim:

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.

SOFTWARE REQUIRED:

Anaconda - Python 3.7

Algorithm:

Step1:

Import the libraries.

Step2:

Use cv2.calcHist to find the histogram of the image.

Step3:

Plot the image and its stem plots using the functions.

Step4:

Equalize the grayscale image using the in-built function cv2.equalizeHist().

Step5:

Display the original and equalized image.

PROGRAM:

Developed By: Syed Abdul Wasih
Register Number: 212221240057

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("image.png")
Color_image = cv2.imread("1.png",-1)
cv2.imshow("Gray Image",Gray_image)
cv2.imshow("Colour Image",Color_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Display the histogram of gray scale image and any one channel histogram from color image:

import numpy as np
import matplotlib.pyplot as plt
gray_hist = cv2.calcHist([Gray_image],[0],None,[256],[0,256])
color_hist = cv2.calcHist([Color_image],[0],None,[256],[0,256])
plt.figure()
plt.imshow(Gray_image)
plt.show()
plt.title("Histogram")
plt.xlabel("Grayscale Value")
plt.ylabel("Pixel Count")
plt.stem(gray_hist)
plt.show()
plt.imshow(Color_image)
plt.show()
plt.title("Histogram of Color Image - Green Channel")
plt.xlabel("Intensity Value")
plt.ylabel("Pixel Count")
plt.stem(color_hist)
plt.show()
cv2.waitKey(0)
cv2.destroyAllWindows()

Write the code to perform histogram equalization of the image.

import cv2
gray_image = cv2.imread("shinchan.jpg",0)
cv2.imshow('Grey Scale Image',gray_image)
equ = cv2.equalizeHist(gray_image)
cv2.imshow("Equalized Image",equ)
cv2.waitKey(0)
cv2.destroyAllWindows

OUTPPUT:

Input Grayscale Image and Color Image

Histogram of Grayscale Image and any channel of Color Image

Histogram Equalization of Grayscale Image

RESULT:

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.

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