使用 NEON 和 OpenMP 加速模板匹配算法

以下是一个使用 NEON 和 OpenMP 实现模板匹配算法的示例代码：

#include <iostream>
#include <vector>
#include <opencv2/opencv.hpp>
#include <omp.h>

void templateMatchingNEON(const cv::Mat& image, const cv::Mat& templ, cv::Mat& result) {
    CV_Assert(image.depth() == CV_8U && templ.depth() == CV_8U);
    CV_Assert(image.channels() == 1 && templ.channels() == 1);

    const int imageWidth = image.cols;
    const int imageHeight = image.rows;
    const int templWidth = templ.cols;
    const int templHeight = templ.rows;
    const int resultWidth = imageWidth - templWidth + 1;
    const int resultHeight = imageHeight - templHeight + 1;

    result.create(resultHeight, resultWidth, CV_32F);

    int i, j, k, l;
    int simdSize = sizeof(float) / sizeof(uint8_t);

    #pragma omp parallel for private(j, k, l) simd
    for (i = 0; i < resultHeight; ++i) {
        for (j = 0; j < resultWidth; j+=simdSize) {
            const uint8_t* imagePtr = image.ptr<uint8_t>(i);
            const uint8_t* templPtr = templ.ptr<uint8_t>(0);
            float* resultPtr = result.ptr<float>(i);

            uint8x8_t vtempl = vld1_u8(templPtr);
            uint8x8_t vimage;
            float32x4_t vsum0 = vdupq_n_f32(0.0f);
            float32x4_t vsum1 = vdupq_n_f32(0.0f);
            
            for (k = 0; k < templHeight; ++k) {
                imagePtr = image.ptr<uint8_t>(i + k) + j;
                templPtr = templ.ptr<uint8_t>(k);

                for (l = 0; l < templWidth; l+=simdSize) {
                    vimage = vld1_u8(imagePtr + l);
                    uint16x8_t vdiff = vsubl_u8(vimage, vtempl);
                    float32x4_t vdiff0 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vdiff)));
                    float32x4_t vdiff1 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vdiff)));
                    vsum0 = vmlaq_f32(vsum0, vdiff0, vdiff0);
                    vsum1 = vmlaq_f32(vsum1, vdiff1, vdiff1);
                }
            }

            vst1q_f32(resultPtr, vaddq_f32(vsum0, vsum1));
        }
    }
}

int main() {
    cv::Mat image = cv::imread('image.png', cv::IMREAD_GRAYSCALE);
    cv::Mat templ = cv::imread('template.png', cv::IMREAD_GRAYSCALE);

    cv::Mat result;
    templateMatchingNEON(image, templ, result);

    cv::imshow('Result', result);
    cv::waitKey(0);

    return 0;
}

注意：上述代码使用了OpenCV和NEON的SIMD指令集来加速模板匹配算法。首先，我们使用NEON指令集来并行计算模板匹配，然后使用OpenMP来并行化对每个像素的处理。在代码中，我们使用了NEON的SIMD指令来进行向量化计算，以提高计算效率。