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【图像处理】OpenCv + Python 实现 Photoshop 中的色彩平衡功能

article 2025/1/6 20:49:35

前言

这是使用 python 和 OpenCv 实现的 Photoshop 中色彩平衡功能的代码，可以设置阴影，高光和中间调的色调参数来调整图片的色彩平衡。

参考文章二也有 python 版本的代码实现，虽然中间调的部分貌似没有实现，但是理论部分讲解还是不错的。

我的代码是基于参考文章一中的 Matlab 代码转写实现的。

代码

import cv2
import numpy as np

def normalize_coeffs(coeffs):
    median_val = sorted(coeffs)[1]
    return np.array([coef - median_val for coef in coeffs])

def highlight_handle(img, highlight_coeffs):
    highlights_alpha = 0.003923 * normalize_coeffs(highlight_coeffs)

    a = np.diag(np.maximum(highlights_alpha, 0)) * np.eye(3)
    b = np.diag(-np.minimum(highlights_alpha, 0)) * (1 - np.eye(3))

    highlights_alpha = np.sum(a + b, axis=0)
    img = img / (1 - highlights_alpha.reshape(1, 1, 3))
    return img

def shadow_handle(img, shadows_coef):
    shadows_alpha = 0.003923 * normalize_coeffs(shadows_coef)

    a = np.diag(-np.minimum(shadows_alpha, 0)) * np.eye(3)
    b = np.diag(np.maximum(shadows_alpha, 0)) * (1 - np.eye(3))
    shadows_alpha = np.sum(a + b, axis=0)

    img = (img - shadows_alpha.reshape(1, 1, 3)) / (1 - shadows_alpha.reshape(1, 1, 3))
    return img

def mid_tone_handle(img, mid_tone_coeffs):  
    mid_tone_alpha = -0.0033944 * normalize_coeffs(mid_tone_coeffs)

    f = np.diag(mid_tone_alpha) * (2 * np.eye(3) - 1)
    mid_tone_gamma = np.exp(np.sum(f, axis=0))

    img = np.power(img, mid_tone_gamma.reshape(1, 1, 3))
    return img

def img_bgr2rgb(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) 
    img = img.astype(np.float32) / 255.0
    img = img.copy()
    return img

def img_rgb2bgr(img):
    img = cv2.normalize(img, None, 0, 255, cv2.NORM_MINMAX)
    img = img.astype(np.uint8)
    img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
    return img

def display(image):
    cv2.namedWindow("img", cv2.WINDOW_NORMAL)
    cv2.imshow("img", image)
    cv2.waitKey()

def main(
        image_path,
        shadow_coefficients,
        mid_tone_coefficients,
        highlight_coefficients
):
    image = cv2.imread(image_path)
    image = img_bgr2rgb(image)
    
    image = highlight_handle(image, highlight_coefficients)
    image = shadow_handle(image, shadow_coefficients)
    image = mid_tone_handle(image, mid_tone_coefficients)
    
    image = np.clip(image, 0, 1)
    image = img_rgb2bgr(image)
    
    display(image)

if __name__ == '__main__':
    main(
        image_path=r"C:\Users\XXXX\Desktop\capture.png",
        shadow_coefficients=[0, 0, 0],
        mid_tone_coefficients=[0, 0, 0],
        highlight_coefficients=[0, 0, 0],
    )