vasanthamukilan / histogram-of-an-images

Histogram-of-an-images

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:

Read the gray and color image using imread()

Step2:

Print the image using imshow().

Step3:

Use calcHist() function to mark the image in graph frequency for gray and color image.

step4:

Use calcHist() function to mark the image in graph frequency for gray and color image.

Step5:

The Histogram of gray scale image and color image is shown.

Program:

# Developed By:Vasanthamukilan M
# Register Number:212222230167

Input Grayscale Image and Color Image

import matplotlib.pyplot as plt
import numpy as np
import cv2
Gray_image = cv2.imread("sea.png")
Color_image = cv2.imread("lake2.jpg")
plt.imshow(Gray_image)
plt.show()
plt.imshow(Color_image)
plt.show()

Histogram of Grayscale Image and any channel of Color Image

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()
plt.imshow(Color_image)
plt.show()
hist1=cv2.calcHist([Color_image], [1], None, [256], [0,256])
plt.figure()
plt.title("Histogram of Color Image - Green Channel")
plt.xlabel("Intensity Value")
plt.ylabel("Pixel Count")
plt.stem (hist1)
plt.show()

Histogram Equalization of Grayscale Image.

plt.imshow(Color_image)
plt.show()
hist1=cv2.calcHist([Color_image], [1], None, [256], [0,256])
plt.figure()
plt.title("Histogram of Color Image - Green Channel")
plt.xlabel("Intensity Value")
plt.ylabel("Pixel Count")
plt.stem (hist1)
plt.show()

Output:

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.