import cv2

import numpy as np

import matplotlib.pyplot as plt

import copy

im = cv2.imread('IMG_2126.PNG', 0)

row = np.zeros((1, im.shape[1]))

im = np.row_stack((row, im, row))

col = np.zeros((im.shape[0], 1))

im = np.column_stack((col, im, col))

rod = 5

K = 100

lamda = 0.1

im_out = copy.deepcopy(im)

def g(grad, k):

return np.exp(-(grad / k) ** 2)

for k in range(rod):

for i in range(1, im.shape[0] - 1):

for j in range(1, im.shape[1] - 1):

grad_N = (im[i - 1][j] - im[i][j]) / 2

grad_S = (im[i + 1][j] - im[i][j]) / 2

grad_W = (im[i][j - 1] - im[i][j]) / 2

grad_E = (im[i][j + 1] - im[i][j]) / 2

im_out[i][j] -= lamda * (g(grad_N, K) * grad_N + g(grad_S, K) * grad_S + g(grad_W, K) * grad_W + g(grad_E, K) * grad_E)

plt.imshow(im_out[1:-1, 1:-1], 'gray')

plt.show()