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:
The value in the given matrix is in the range of [0, 255].
The length and width of the given matrix are in the range of [1, 150].
Solution
class Solution {
public:
vector<vector<int>> imageSmoother(vector<vector<int>>& M) {
int m = M.size();
int n = M[0].size();
vector<vector<int>> ans(m, vector<int>(n));
vector<pair<int, int>> diffs = {
{-1, -1}, {-1, 0}, {-1, 1}, {0, -1}, {0, 1}, {1, -1}, {1, 0}, {1, 1}
};
for(int i = 0; i < m; ++i){
for(int j = 0; j < n; ++j){
int sum = M[i][j];
int k = 1;
for(auto p : diffs){
int x = i + p.first;
int y = j + p.second;
if(0 <= x && x < m && 0 <= y && y < n){
++k;
sum += M[x][y];
}
}
ans[i][j] = sum / k;
}
}
return ans;
}
};