[Leetcode] 661. Image Smoother 解题报告

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本文介绍了一个简单的图像平滑算法，该算法将每个像素的颜色值替换为周围8个像素及自身的平均值（向下取整）。通过具体示例展示了如何实现这一算法，并提供了C++代码示例。

题目：

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].

思路：

练手题目，哈哈。

代码：

class Solution {
public:
    vector<vector<int>> imageSmoother(vector<vector<int>>& M) {
        if (M.size() == 0) {
            return {};
        }
        int row_num = M.size(), col_num = M[0].size();
        vector<vector<int>> N(row_num, vector<int>(col_num, 0));
        for (int r = 0; r < row_num; ++r) {
            for (int c = 0; c < col_num; ++c) {
                N[r][c] = getAverage(M, r, c);
            }
        }
        return N;
    }
private:
    int getAverage(vector<vector<int>> &M, int r, int c) {
        int row_num = M.size(), col_num = M[0].size();
        int count = 0, sum = 0;
        for (int i = r - 1; i <= r + 1; ++i) {
            for (int j = c - 1; j <= c + 1; ++j) {
                if (i >= 0 && i < row_num && j >= 0 && j < col_num) {
                    sum += M[i][j];
                    ++count;
                }
            }
        }
        return sum / count;
    }
};