用python写阶数为n的方形中值滤波器及十字形中值滤波器

我可以为您提供相应的代码和算法解释，以下是阶数为n的方形中值滤波器的Python代码：

import numpy as np

def square_median_filter(img, n):
    # Add padding to the input image to handle border pixels
    pad_width = n // 2
    padded_img = np.pad(img, pad_width, mode='constant', constant_values=0)
    output_img = np.zeros_like(img)
    
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            # Extract the n x n neighborhood around the current pixel
            neighborhood = padded_img[i:i+n, j:j+n]
            # Compute the median of the neighborhood and assign it to the output
            output_img[i, j] = np.median(neighborhood)
            
    return output_img

对于十字形中值滤波器，可以使用类似的方法实现，只需要在提取邻域时选择横向和纵向的像素，具体代码如下：

import numpy as np

def cross_median_filter(img, n):
    # Add padding to the input image to handle border pixels
    pad_width = n // 2
    padded_img = np.pad(img, pad_width, mode='constant', constant_values=0)
    output_img = np.zeros_like(img)
    
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            # Extract the n pixels above and below the current pixel, and to the left and right of it
            neighborhood = np.concatenate((padded_img[i-pad_width:i, j], padded_img[i+1:i+pad_width+1, j], 
                                            padded_img[i, j-pad_width:j], padded_img[i, j+1:j+pad_width+1]))
            # Compute the median of the neighborhood and assign it to the output
            output_img[i, j] = np.median(neighborhood)
            
    return output_img

以上两个函数均采用了numpy库中的一些函数，需要在代码中先导入numpy库。