void WritePicToExcel(string name, cv::Mat pic)
{
    // 我這里寫了斷言，可以根據需要自己調整
	CV_Assert(pic.type() == CV_32FC1);
	ofstream outfile(name);
	int row = pic.rows;
	int col = pic.cols;
	for (int i = 0; i < row; i++)
	{
        // 采用指針讀取Mat矩陣的方式提速
		float *p = pic.ptr<float>(i);
		for (int j = 0; j < col; j++)
		{
            // 若需要保存的數據是非nan值，則正常保存；若為nan值，則保存字符“nan”
			if (p[j] == p[j])
			{
				outfile << p[j] << (j == (col - 1) ? '\n' : '\t');
			}
			else {
				outfile << "nan" << (j == (col - 1) ? '\n' : '\t');
			}
			
		}
	}
	outfile.close();
}

#include<iostream>
#include<fstream>
#include<opencv2/opencv.hpp>
using namespace std;
void WritePicToExcel(string name, cv::Mat pic);
int main()
{
	cv::Mat pic = cv::Mat::zeros(1000, 1000, CV_32FC1);
	for (int i = 0; i < pic.rows; i++)
	{
		for (int j = 0; j < pic.cols; j++)
		{
			pic.at<float>(i, j) = rand() % 255;
		}
	}
    // 人為設置一個nan值檢驗是否可以有效保存
	pic.at<float>(1, 2) = nan("");
    // 輸入的string為保存的文件名，函數其實還可以加點文件格式的判斷，有興趣的自己改進下吧
	WritePicToExcel("test1.xls", pic);
	return 0;
}
void WritePicToExcel(string name, cv::Mat pic)
{
	CV_Assert(pic.type() == CV_32FC1);
	ofstream outfile(name);
	int row = pic.rows;
	int col = pic.cols;
	for (int i = 0; i < row; i++)
	{
		float *p = pic.ptr<float>(i);
		for (int j = 0; j < col; j++)
		{
			if (p[j] == p[j])
			{
				outfile << p[j] << (j == (col - 1) ? '\n' : '\t');
			}
			else {
				outfile << "nan" << (j == (col - 1) ? '\n' : '\t');
			}
			
		}
	}
	outfile.close();
}