input: Write a python function that takes a grayscale image represented by an m x n grid (where each element is an intensity ranging from 0 to 255) and a non-negative integer threshold. The function should return a new m x n grid where each cell contains the average intensity of regions consisting of 3 x 3 subgrids in which the absolute difference between any two adjacent pixels is less than or equal to the threshold. The average intensity is computed by considering the rounded-down average intensities of regions a pixel belongs to. If a pixel does not belong to any region, its value remains unchanged.
  
  Examples:
  >>> image = [[5,6,7,10],[8,9,10,10],[11,12,13,10]], threshold = 3
  [[9,9,9,9],[9,9,9,9],[9,9,9,9]]
  >>> image = [[10,20,30],[15,25,35],[20,30,40],[25,35,45]], threshold = 12
  [[25,25,25],[27,27,27],[27,27,27],[30,30,30]]
  >>> image = [[5,6,7],[8,9,10],[11,12,13]], threshold = 1
  [[5,6,7],[8,9,10],[11,12,13]]
  
  Constraints:
  3 <= n, m <= 500
  0 <= image[i][j] <= 255
  0 <= threshold <= 255
output: def process_image(image, threshold):
      from collections import deque
      m, n = len(image), len(image[0])
      result = [[image[i][j] for j in range(n)] for i in range(m)]
      directions = [(-1, 0), (1, 0), (0, -1), (0, 1)]
  
      def bfs(i, j, visited):
          queue = deque([(i, j)])
          region = [(i, j)]
          total_intensity = image[i][j]
          count = 1
          visited.add((i, j))
          
          while queue:
              x, y = queue.popleft()
              for d in directions:
                  ni, nj = x + d[0], y + d[1]
                  if 0 <= ni < m and 0 <= nj < n and (ni, nj) not in visited and abs(image[ni][nj] - image[x][y]) <= threshold:
                      visited.add((ni, nj))
                      queue.append((ni, nj))
                      region.append((ni, nj))
                      total_intensity += image[ni][nj]
                      count += 1
          
          avg_intensity = total_intensity // count
          for x, y in region:
              result[x][y] = avg_intensity
  
      visited = set()
      for i in range(m):
          for j in range(n):
              if (i, j) not in visited:
                  bfs(i, j, visited)
  
      return result