python计算两个图像的互信息

我们常用互信息来衡量两个图像的相似程度。互信息的计算方式如下：使用python中的numpy包或者sklearn可以很方便的计算互信息，计算代码如下：import cv2import numpy as npimport sklearn.metrics as skmdef hxx_forward(x, y):return skm.mutual_info_score(x, y)def hxx(x, y

sihaiyinan

10040人浏览 · 2021-01-04 19:28:16

sihaiyinan · 2021-01-04 19:28:16 发布

我们常用互信息来衡量两个图像的相似程度。互信息的计算方式如下：

使用python中的numpy包或者sklearn可以很方便的计算互信息，计算代码如下：


import cv2
import numpy as np
import sklearn.metrics as skm


def hxx_forward(x, y):
    return skm.mutual_info_score(x, y)

def hxx(x, y):
    size = x.shape[-1]
    px = np.histogram(x, 256, (0, 255))[0] / size
    py = np.histogram(y, 256, (0, 255))[0] / size
    hx = - np.sum(px * np.log(px + 1e-8))
    hy = - np.sum(py * np.log(py + 1e-8))

    hxy = np.histogram2d(x, y, 256, [[0, 255], [0, 255]])[0]
    hxy /= (1.0 * size)
    hxy = - np.sum(hxy * np.log(hxy + 1e-8))

    r = hx + hy - hxy
    return r


img1 = cv2.imread("F:/BYSY/ACCESS/ImageMatch/1.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("F:/BYSY/ACCESS/ImageMatch/1.png", cv2.IMREAD_GRAYSCALE)

x = np.reshape(img1, -1)
y = np.reshape(img2, -1)

print(hxx_forward(x, y))
print(hxx(x, y))

经验证，两种方法计算结果相同