Given a 2D binary matrix filled with 0's and 1's, find the largest square containing all 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 0Return 4.
Credits:
Special thanks to @Freezen for adding this problem and creating all test cases.
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思路:
1.动态规划的题,可以维护一个ret[m*n]的整数数组去表示matrix各元素的状态;
2.首先边界i=0,j=0:第一行和第一列与matrix相同(即ret[i][0] = matrix[i][0],ret[0][i] = matrix[0][i]);
3.当i>0,j>0时,
如果matrix[i][j]=='0',ret[i][j]=0;
如果matrix[i][j]=='1',ret[i][j]由左上角的3个值推出;
推导公式,即状态转移方程为:ret[i][j]=min(ret[i-1][j],ret[i][j-1],ret[i-1][j-1]) + 1;
code:
class Solution { public: int maximalSquare(vector<vector<char>>& matrix) { int m = matrix.size(); if(m==0) return 0; int n = matrix[0].size(); vector<vector<int>> ret(m, vector<int>(n,0)); int maxSize = 0; for(int i=0;i<m;i++) { ret[i][0] = matrix[i][0]-'0'; maxSize = max(ret[i][0], maxSize); } for(int j=0;j<n;j++) { ret[0][j] = matrix[0][j]-'0'; maxSize = max(ret[0][j], maxSize); } for(int i=1;i<m;i++) for(int j=1;j<n;j++) { if(matrix[i][j]=='1') ret[i][j] = min(ret[i-1][j],min(ret[i][j-1],ret[i-1][j-1])) + 1; maxSize = max(ret[i][j], maxSize); } return maxSize*maxSize; } };
当然还可以有一些空间上的优化:Easy DP solution in C++ with detailed explanations (8ms, O(n^2) time and O(n) space)