661. Image Smoother 图像平滑化


Given a 2D integer matrix M representing the gray scale of an image, you need to design a smoother to make the gray scale of each cell becomes the average gray scale (rounding down) of all the 8 surrounding cells and itself. If a cell has less than 8 surrounding cells, then use as many as you can.

Example 1:

Input:
[[1,1,1],
 [1,0,1],
 [1,1,1]]
Output:
[[0, 0, 0],
 [0, 0, 0],
 [0, 0, 0]]
Explanation:
For the point (0,0), (0,2), (2,0), (2,2): floor(3/4) = floor(0.75) = 0
For the point (0,1), (1,0), (1,2), (2,1): floor(5/6) = floor(0.83333333) = 0
For the point (1,1): floor(8/9) = floor(0.88888889) = 0

Note:

  1. The value in the given matrix is in the range of [0, 255].
  2. The length and width of the given matrix are in the range of [1, 150].

给定一个表示图像灰度的二维整数矩阵M,您需要设计一个更平滑的方式,使每个单元格的灰度值成为所有8个周围单元格本身的平均灰度(舍入)。如果一个单元格具有小于8个周围的单元格,那么可以使用尽可能多的单元格。

  1. class Solution(object):
  2. def imageSmoother(self, M):
  3. import math
  4. result = []
  5. for i in range(len(M)):
  6. row = []
  7. for j in range(len(M[i])):
  8. pos = [
  9. [i - 1, j - 1], [i - 1, j], [i - 1, j + 1],
  10. [i, j - 1], [i, j], [i, j + 1],
  11. [i + 1, j - 1], [i + 1, j], [i + 1, j + 1]
  12. ]
  13. near = []
  14. for item in pos:
  15. if item[0] >= 0 and item[0] < len(M) and item[1] >= 0 and item[1] < len(M[i]):
  16. near.append(M[item[0]][item[1]])
  17. row.append(int(sum(near) / len(near)))
  18. result.append(row)
  19. return result





原文地址:https://www.cnblogs.com/xiejunzhao/p/7430241.html