I am trying to change the L*
values of an image in L*a*b*
color space. But the resultant image is not what I expected. How should I change brightness of the image using the L*a*b*
values?
My Code:
imd = np.asarray(ibuffer).copy()
imgb = cv2.cvtColor(imd, cv2.COLOR_BGR2Lab)
value = 255 * (int(bvalue)/100)
imgb[:,:,0] += int(value)
imgb = cv2.cvtColor(imgb,cv2.COLOR_LAB2BGR)
photo = Image.fromarray(imgb)
photo = resize(photo)
photo = ImageTk.PhotoImage(photo)
canvas.photo = photo
canvas.create_image(0,0,anchor="nw",image = photo)
Original image:
Edited image:
You're adding some value to the already existing L*
value, which will cause integer overflows, thus unexpected behaviour. What you actually want – at least, to my understanding – is to have a scaling between 0 % – 100 % of the original L*
value, so something like this:
Therefore, just multiply the original L*
value with the percentage you input (full code to reproduce the above output):
import cv2
import matplotlib.pyplot as plt
import numpy as np
img = cv2.imread('path/to/your/image.png')
img_lab = cv2.cvtColor(img, cv2.COLOR_BGR2Lab)
plt.figure(0, figsize=(18, 9))
for i, a in enumerate([0, 20, 40, 60, 80, 100]):
img_mod = img_lab.copy()
img_mod[:, :, 0] = (a/100 * img_mod[:, :, 0]).astype(np.uint8)
img_mod = cv2.cvtColor(img_mod, cv2.COLOR_Lab2BGR)
plt.subplot(2, 3, i+1)
plt.imshow(img_mod[:, :, [2, 1, 0]])
plt.title('L = {}'.format(a))
plt.tight_layout()
plt.show()
----------------------------------------
System information
----------------------------------------
Platform: Windows-10-10.0.16299-SP0
Python: 3.8.5
Matplotlib: 3.3.3
NumPy: 1.19.5
OpenCV: 4.5.1
----------------------------------------