221. Maximal Square
题目:
Given a 2D binary matrix filled with 0's and 1's, find the largest square containing only 1's and return its area.
For example :
given the following matrix:
1 0 1 0 0
1 0 1 1 1
1 1 1 1 1
1 0 0 1 0
Return 4.
Credits:
Special thanks to @Freezen for adding this problem and creating all test cases.
代码如下:
class Solution {
public:
int maximalSquare(vector<vector<char>>& matrix) {
int max_side = 0;
int row = matrix.size();
if (row == 0) return max_side;
int col = matrix[0].size();
vector<vector<int>> visit(row, vector<int>(col, 0));
for (int i = 0; i < row; i++) {
if (matrix[i][0] == '1') {
visit[i][0] = 1;
max_side = 1;
}
}
for (int j = 0; j < col; j++) {
if (matrix[0][j] == '1') {
visit[0][j] = 1;
max_side = 1;
}
}
for (int i = 1; i < row; i++) {
for (int j = 1; j < col; j++) {
if (matrix[i][j] == '1') {
visit[i][j] = min(visit[i - 1][j], min(visit[i][j - 1], visit[i - 1][j - 1])) + 1;
max_side = max(visit[i][j], max_side);
}
}
}
return max_side * max_side;
}
};
解题思路:
- 利用动态规划,从左上角开始,当前点若为1,那么正方形边长为这个点的左边、左上、上面点的最小值加1(短板效应),因为边数取决于最短的那个,若有一个为0,则边为1;
- 利用max_side来记录目前为止的最大边长;
- 一开始遍历第0行和第0列,若有任意一个值为1,那么max_side至少为1;
- 接下来利用动态转换方程求解即可。