I am trying to linearly scale an image so the whole greyscale range is used. This is to improve the lighting of the shot. When plotting the histogram however I don't know how to get the scaled histogram so that its smoother so it's a curve as aspired to discrete bins. Any tips or points would be much appreciated.
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread(r'/Users/harold/Documents/Academia/Nottingham Uni/Year 4/ImageProcessing/Imaging_Task_Sheet/PointImage.jpeg', cv.IMREAD_GRAYSCALE)
img_s = img/255
img_s = img_s / np.max(img_s)
img_s = img_s*255
histogram = cv.calcHist([img], [0], None, [256], [0, 256])
histogram1 = cv.calcHist([img_s.astype('uint8')], [0], None, [256], [0, 256])
plt.figure()
plt.title("Grayscale Histogram")
plt.xlabel("grayscale value")
plt.ylabel("pixels")
plt.plot(histogram, label='Original Image') # <- or here
plt.plot(histogram1, label='Equalised Image') # <- or here
The histogram produced is:
Which is from this picture:
