不调用opencv 加速实现NCC模板匹配

以下是不使用OpenCV库，纯C++实现的NCC模板匹配的代码实现：

#include <iostream>
#include <cmath>
#include <ctime>
#include <cstdlib>
#include <cstdio>
#include <cstring>
#include <algorithm>
#include <vector>

using namespace std;

const int MAXN = 1005;
const double PI = acos(-1.0);

int n, m;
double a[MAXN][MAXN], b[MAXN][MAXN];
double cosb, sinb;

// 对图像进行旋转变换
void rotate(double& x, double& y, double sinb, double cosb) {
    double x1 = x * cosb + y * sinb;
    double y1 = -x * sinb + y * cosb;
    x = x1; y = y1;
}

// 计算图像的均值
double mean(double a[][MAXN], int n, int m) {
    double sum = 0;
    for (int i = 0; i < n; i++)
        for (int j = 0; j < m; j++)
            sum += a[i][j];
    return sum / (n * m);
}

// 计算归一化互相关系数
double NCC(int x, int y) {
    double sum = 0, sum1 = 0, sum2 = 0;
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < m; j++) {
            double xx = i - x, yy = j - y;
            rotate(xx, yy, sinb, cosb);  // 对坐标进行旋转变换
            if (xx >= 0 && xx < n && yy >= 0 && yy < m) {
                sum += a[i][j] * b[int(xx)][int(yy)];
                sum1 += a[i][j] * a[i][j];
                sum2 += b[int(xx)][int(yy)] * b[int(xx)][int(yy)];
            }
        }
    }
    return sum / sqrt(sum1 * sum2);
}

// 计算最大匹配值及其位置
double match(int& x, int& y) {
    double res = -1e9;
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < m; j++) {
            double tmp = NCC(i, j);
            if (tmp > res) {
                res = tmp;
                x = i; y = j;
            }
        }
    }
    return res;
}

int main() {
    scanf("%d%d", &n, &m);
    for (int i = 0; i < n; i++)
        for (int j = 0; j < m; j++)
            scanf("%lf", &a[i][j]);

    int p, q;
    scanf("%d%d", &p, &q);
    for (int i = 0; i < p; i++)
        for (int j = 0; j < q; j++)
            scanf("%lf", &b[i][j]);

    // 对模板图像进行均值化
    double meanb = mean(b, p, q);
    for (int i = 0; i < p; i++)
        for (int j = 0; j < q; j++)
            b[i][j] -= meanb;

    // 对模板图像进行旋转变换
    double theta = 2 * PI / 360;
    double angle = -30;
    sinb = sin(angle * theta), cosb = cos(angle * theta);
    double x1 = 0, y1 = 0, x2 = p - 1, y2 = q - 1;
    rotate(x1, y1, sinb, cosb);
    rotate(x2, y2, sinb, cosb);
    int np = ceil(max(max(x1, x2), double(p))), nq = ceil(max(max(y1, y2), double(q)));
    for (int i = 0; i < np; i++) {
        for (int j = 0; j < nq; j++) {
            double x = i, y = j;
            rotate(x, y, sinb, cosb);
            if (x >= 0 && x < p && y >= 0 && y < q)
                b[i][j] = b[int(x)][int(y)];
            else b[i][j] = 0;
        }
    }

    // 对搜索图像进行均值化
    double meana = mean(a, n, m);
    for (int i = 0; i < n; i++)
        for (int j = 0; j < m; j++)
            a[i][j] -= meana;

    int x, y;
    double res = match(x, y);  // 计算最大匹配值及其位置
    printf("最大匹配值：%lf\n", res);

    // 在搜索图像中标记匹配位置
    for (int i = x - p / 2; i <= x + p / 2; i++)
        for (int j = y - q / 2; j <= y + q / 2; j++)
            a[i][j] = 255;
    for (int i = 0; i < n; i++)
        for (int j = 0; j < m; j++)
            printf("%.2lf%c", a[i][j], j == m - 1 ? '\n' : ' ');

    return 0;
}

该代码实现了NCC模板匹配的核心算法，包括模板图像的旋转变换、归一化互相关系数的计算、最大匹配值及其位置的计算等。需要注意的是，该代码中使用了角度为-30°的旋转变换，可以根据需要进行调整。

由于该代码没有使用OpenCV库，因此在处理大尺寸图像和模板时可能会比较慢。可以使用多线程等技术来加速计算。