Python实现图像直方图均衡化算法

---

title: "Python实现图像直方图均衡化算法"

date: 2018-06-12T17:10:48+08:00

tags: [""]

categories: ["python"]

---

效果图

代码

#!/usr/bin/env python3

# coding=utf-8

import matplotlib.image as mpimg

from matplotlib import pyplot as plt

import sys

import numpy as np

def equalization(gray_value):

    """

    传入灰度值，对灰度值做均衡化，不需要返回，直接修改传入的参数

    :param gray_value:

    """

    # 统计灰度直方图

    gray = np.zeros(256)

    row, column = gray_value.shape

    for i in range(row):

        for j in range(column):

            gray[gray_value[i][j]] += 1

    # 计算灰度占比

    gray /= (row * column)

    # 显示灰度直方图

    plt.subplot(2, 2, 2)

    plt.plot(gray)

    cumsum = np.cumsum(gray)  # 计算累积和

    # 均衡化

    # equa_t[i]=j表示原灰度值i经过均衡化后转化为灰度值j

    # 255×累积和四舍五入为int型

    equa_t = np.array((255 * cumsum + 0.5)).astype(np.int32)

    # 统计均衡化后的灰度数量

    equa_gray = np.zeros(256)

    for i in range(256):

        equa_gray[equa_t[i]] += gray[i]

    # 显示均衡化后的直方图

    plt.subplot(2, 2, 4)

    plt.plot(equa_gray)

    # 对原灰度矩阵做均衡化

    for i in range(row):

        for j in range(column):

            gray_value[i][j] = equa_t[gray_value[i][j]]

def run(img_path):

    img_array = mpimg.imread(img_path)

    plt.subplot(2, 2, 1)

    plt.imshow(img_array)

    img_array *= 255

    img_array = img_array.astype(np.int32)

    equalization(img_array[:, :, 0])

    equalization(img_array[:, :, 1])

    equalization(img_array[:, :, 2])

    img_array = img_array.astype(np.float64)

    img_array /= 255

    plt.subplot(2, 2, 3)

    plt.imshow(img_array)

if __name__ == "__main__":

    if sys.argv.__len__() <= 1:

        png = input("请输入要处理的图片名:\n")

    else:

        png = sys.argv[1]

    run(png)

    plt.show()