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How to use Python to perform lighting compensation on pictures
Abstract:
For digital image processing, uneven lighting is one of the common problems. This article will introduce how to use the OpenCV library in the Python programming language to perform lighting compensation on pictures. We will extract the lighting information of the image, and then adjust the brightness and contrast of the image based on this information to achieve the effect of uniform lighting.
import cv2 import numpy as np import matplotlib.pyplot as plt
image = cv2.imread('image.jpg',1) cv2.imshow('Original Image', image) cv2.waitKey(0) cv2.destroyAllWindows()
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) mean = np.mean(gray_image)
alpha = 1.0 / mean beta = 0 light_compensated_image = cv2.convertScaleAbs(image, alpha=alpha, beta=beta)
cv2.imshow('Light Compensated Image', light_compensated_image) cv2.waitKey(0) cv2.destroyAllWindows() cv2.imwrite('light_compensated_image.jpg', light_compensated_image)
Conclusion:
This article demonstrates the process of lighting compensation for images by using Python and the OpenCV library. Uneven lighting is a common problem in digital image processing, but by extracting lighting information and adjusting the brightness and contrast of the image, we can effectively achieve uniform lighting effects. As a powerful programming language, Python provides various image processing tools and libraries, making illumination compensation simpler and more efficient.
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