Python实现RGB和Lab颜色空间互转
/rubund/debian-home-assistant/blob/1a3e8f7e4b9ddec60a4380e141fb327d03ac69b5/homeassistant/util/color.py
在网上找了一圈，只找到C++版本的，有个python版本的只有RGB转Lab，只好自己写了。C++版本传送门，这里把原理已经写的很清楚了，我只是比葫芦画瓢的写个python版本，没做任何优化。只有一点需要小心，opencv读取的图像格式是[b,g,r]，剩下的就是按公式写代码了。
# -*- coding: utf-8 -*-# 提供图像处理辅助函数，色彩空间转换# @Author : BQH# @File : tools.py# @Date : -11-07import numpy as npimport cv2# region 辅助函数# RGB2XYZ空间的系数矩阵M = np.array([[0.412453, 0.357580, 0.180423],[0.212671, 0.715160, 0.072169],[0.019334, 0.119193, 0.950227]])# im_channel取值范围：[0,1]def f(im_channel):return np.power(im_channel, 1 / 3) if im_channel > 0.008856 else 7.787 * im_channel + 0.137931def anti_f(im_channel):return np.power(im_channel, 3) if im_channel > 0.206893 else (im_channel - 0.137931) / 7.787# endregion# region RGB 转 Lab# 像素值RGB转XYZ空间，pixel格式:(B,G,R)# 返回XYZ空间下的值def __rgb2xyz__(pixel):b, g, r = pixel[0], pixel[1], pixel[2]rgb = np.array([r, g, b])# rgb = rgb / 255.0# RGB = np.array([gamma(c) for c in rgb])XYZ = np.dot(M, rgb.T)XYZ = XYZ / 255.0return (XYZ[0] / 0.95047, XYZ[1] / 1.0, XYZ[2] / 1.08883)def __xyz2lab__(xyz):"""XYZ空间转Lab空间:param xyz: 像素xyz空间下的值:return: 返回Lab空间下的值"""F_XYZ = [f(x) for x in xyz]L = 116 * F_XYZ[1] - 16 if xyz[1] > 0.008856 else 903.3 * xyz[1]a = 500 * (F_XYZ[0] - F_XYZ[1])b = 200 * (F_XYZ[1] - F_XYZ[2])return (L, a, b)def RGB2Lab(pixel):"""RGB空间转Lab空间:param pixel: RGB空间像素值，格式：[G,B,R]:return: 返回Lab空间下的值"""xyz = __rgb2xyz__(pixel)Lab = __xyz2lab__(xyz)return Lab# endregion# region Lab 转 RGBdef __lab2xyz__(Lab):fY = (Lab[0] + 16.0) / 116.0fX = Lab[1] / 500.0 + fYfZ = fY - Lab[2] / 200.0x = anti_f(fX)y = anti_f(fY)z = anti_f(fZ)x = x * 0.95047y = y * 1.0z = z * 1.0883return (x, y, z)def __xyz2rgb(xyz):xyz = np.array(xyz)xyz = xyz * 255rgb = np.dot(np.linalg.inv(M), xyz.T)# rgb = rgb * 255rgb = np.uint8(np.clip(rgb, 0, 255))return rgbdef Lab2RGB(Lab):xyz = __lab2xyz__(Lab)rgb = __xyz2rgb(xyz)return rgb# endregionif __name__ == '__main__':img = cv2.imread(r'E:\code\collor_recorrect\test_1.jpg')w = img.shape[0]h = img.shape[1]img_new = np.zeros((w,h,3))lab = np.zeros((w,h,3))for i in range(w):for j in range(h):Lab = RGB2Lab(img[i,j])lab[i, j] = (Lab[0], Lab[1], Lab[2])for i in range(w):for j in range(h):rgb = Lab2RGB(lab[i,j])img_new[i, j] = (rgb[2], rgb[1], rgb[0])cv2.imwrite(r'E:\code\collor_recorrect\test.jpg', img_new)
