用python代码实现自适应中值滤波器去除灰度图像的椒盐噪声，不调用openCV库

以下是使用python代码实现自适应中值滤波器去除灰度图像的椒盐噪声：

import numpy as np
from PIL import Image

# 定义自适应中值滤波器函数
def adaptive_median_filter(img, kernel_size):
    # 获取图像的宽度和高度
    width, height = img.shape

    # 计算kernel_size的一半
    half_kernel_size = kernel_size // 2

    # 创建一个与原始图像相同大小的结果图像
    result_img = np.zeros_like(img)

    # 遍历图像的每个像素
    for i in range(width):
        for j in range(height):
            # 获取kernel_size内的像素值
            pixel_values = []
            for m in range(-half_kernel_size, half_kernel_size + 1):
                for n in range(-half_kernel_size, half_kernel_size + 1):
                    # 判断像素是否在图像边界内
                    if i + m >= 0 and i + m < width and j + n >= 0 and j + n < height:
                        pixel_values.append(img[i + m][j + n])

            # 对像素值进行排序
            pixel_values.sort()

            # 获取中值
            median_value = pixel_values[len(pixel_values) // 2]

            # 获取最大和最小的像素值
            z_min = pixel_values[0]
            z_max = pixel_values[-1]

            # 获取中心像素值
            z_med = img[i][j]

            # 判断z_med是否在[z_min, z_max]之间
            if z_min < z_med < z_max:
                result_img[i][j] = z_med
            else:
                # 增加kernel_size的大小
                kernel_size += 2
                half_kernel_size = kernel_size // 2

                # 如果kernel_size大于图像的大小，就返回原始像素值
                if kernel_size > min(width, height):
                    result_img[i][j] = z_med
                else:
                    # 递归调用自适应中值滤波器
                    return adaptive_median_filter(img, kernel_size)

    return result_img


# 读取图像
img = Image.open('lena.jpg').convert('L')
img = np.array(img)

# 添加椒盐噪声
salt_vs_pepper_ratio = 0.05  # 盐和椒的比例
noise_img = np.copy(img)
salt_vs_pepper_amount = int(salt_vs_pepper_ratio * img.shape[0] * img.shape[1])
salt_coords = [np.random.randint(0, i - 1, salt_vs_pepper_amount) for i in img.shape]
pepper_coords = [np.random.randint(0, i - 1, salt_vs_pepper_amount) for i in img.shape]
noise_img[salt_coords] = 255
noise_img[pepper_coords] = 0

# 使用自适应中值滤波器去除椒盐噪声
filtered_img = adaptive_median_filter(noise_img, 3)

# 显示图像
Image.fromarray(img).show()
Image.fromarray(noise_img).show()
Image.fromarray(filtered_img).show()

这段代码首先读取一张灰度图像，然后添加椒盐噪声。接下来，它使用自适应中值滤波器去除椒盐噪声，并将结果图像显示出来。