一维熵

import cv2
import matplotlib.pyplot as plt
import numpy as np
import math
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
def calc_array():
    img=cv2.imread('C:/Users/xpp/Desktop/Lena.png',0)#读取图像
    hist_cv=cv2.calcHist([img],[0],None,[256],[0,256])#[0,256]的范围是0~255
    plt.subplot(231)
    plt.axis('off')
    plt.title('原始图像')
    plt.imshow(img,cmap='gray')
    plt.subplot(232)
    plt.plot(hist_cv)
    plt.show()
    P=hist_cv/(len(img)*len(img[0]))#概率
    E=np.sum([p *np.log2(1/p) for p in P])
    print(E)
calc_array()