使用getRotationMatrix2D创建变换矩阵，通过SIMD指令集加速warpAffine算子参数WARP_INVERSE_MAP效果的C++例程

以下是使用SIMD指令集加速warpAffine算子参数WARP_INVERSE_MAP效果的C++例程：

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/core/hal/intrin.hpp>

using namespace cv;

#define BLOCK_SIZE 4

void warpAffineInverseMap_SIMD(const Mat& src, Mat& dst, const Mat& M)
{
    CV_Assert(src.type() == CV_8UC1);

    int w = src.cols, h = src.rows;
    dst.create(h, w, CV_8UC1);

    float M0 = static_cast<float>(M.at<double>(0, 0));
    float M1 = static_cast<float>(M.at<double>(0, 1));
    float M2 = static_cast<float>(M.at<double>(0, 2));
    float M3 = static_cast<float>(M.at<double>(1, 0));
    float M4 = static_cast<float>(M.at<double>(1, 1));
    float M5 = static_cast<float>(M.at<double>(1, 2));

    __m128 m0 = _mm_set_ps(M0, M0, M0, M0);
    __m128 m1 = _mm_set_ps(M1, M1, M1, M1);
    __m128 m2 = _mm_set_ps(M2, M2, M2, M2);
    __m128 m3 = _mm_set_ps(M3, M3, M3, M3);
    __m128 m4 = _mm_set_ps(M4, M4, M4, M4);
    __m128 m5 = _mm_set_ps(M5, M5, M5, M5);

    int x, y;

    for (y = 0; y < h; y += BLOCK_SIZE) {
        for (x = 0; x < w; x += 4) {
            __m128 fx = _mm_set_ps(x + 3, x + 2, x + 1, x);
            __m128 fy = _mm_set_ps(y + 3, y + 2, y + 1, y);

            __m128 rx = _mm_add_ps(_mm_add_ps(_mm_mul_ps(fx, m0), _mm_mul_ps(fy, m1)), m2);
            __m128 ry = _mm_add_ps(_mm_add_ps(_mm_mul_ps(fx, m3), _mm_mul_ps(fy, m4)), m5);

            __m128i ix = _mm_cvtps_epi32(rx);
            __m128i iy = _mm_cvtps_epi32(ry);

            __m128i mask_x = _mm_cmplt_epi32(ix, _mm_set1_epi32(0));
            __m128i mask_y = _mm_cmplt_epi32(iy, _mm_set1_epi32(0));
            __m128i mask = _mm_or_si128(mask_x, mask_y);

            ix = _mm_andnot_si128(mask, ix);
            iy = _mm_andnot_si128(mask, iy);

            __m128i mask_x2 = _mm_cmpgt_epi32(ix, _mm_set1_epi32(w - 1));
            __m128i mask_y2 = _mm_cmpgt_epi32(iy, _mm_set1_epi32(h - 1));
            __m128i mask2 = _mm_or_si128(mask_x2, mask_y2);

            ix = _mm_andnot_si128(mask2, ix);
            iy = _mm_andnot_si128(mask2, iy);

            __m128i a0 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[0]) + ix[0])), _mm_setzero_si128());
            __m128i a1 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[1]) + ix[1])), _mm_setzero_si128());
            __m128i a2 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[2]) + ix[2])), _mm_setzero_si128());
            __m128i a3 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[3]) + ix[3])), _mm_setzero_si128());

            __m128i b0 = _mm_unpackhi_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[0]) + ix[0])), _mm_setzero_si128());
            __m128i b1 = _mm_unpackhi_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[1]) + ix[1])), _mm_setzero_si128());
            __m128i b2 = _mm_unpackhi_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[2]) + ix[2])), _mm_setzero_si128());
            __m128i b3 = _mm_unpackhi_epi8(_mm_loadl_epi64((const __m128i*)(src.ptr(iy[3]) + ix[3])), _mm_setzero_si128());

            __m128i c0 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(a0, b0), 1), _mm_setzero_si128());
            __m128i c1 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(a1, b1), 1), _mm_setzero_si128());
            __m128i c2 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(a2, b2), 1), _mm_setzero_si128());
            __m128i c3 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(a3, b3), 1), _mm_setzero_si128());

            __m128i d0 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(c0, c1), 1), _mm_setzero_si128());
            __m128i d1 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(c2, c3), 1), _mm_setzero_si128());

            __m128i e0 = _mm_packus_epi16(_mm_srli_epi16(_mm_add_epi16(d0, d1), 1), _mm_setzero_si128());

            *(int*)(dst.ptr(y) + x) = e0[0];
            *(int*)(dst.ptr(y + 1) + x) = e0[1];
            *(int*)(dst.ptr(y + 2) + x) = e0[2];
            *(int*)(dst.ptr(y + 3) + x) = e0[3];
        }
    }
}

int main()
{
    Mat src = imread("test.png", IMREAD_GRAYSCALE);
    if (src.empty()) {
        std::cerr << "failed to open image" << std::endl;
        return -1;
    }

    Mat dst;
    Mat M = getRotationMatrix2D(Point(src.cols / 2, src.rows / 2), 45, 1);
    warpAffineInverseMap_SIMD(src, dst, M);

    imshow("src", src);
    imshow("dst", dst);
    waitKey();

    return 0;
}

其中，warpAffineInverseMap_SIMD函数使用了SSE指令集来加速像素坐标的计算和图像插值的实现。这里使用了4x4的块大小来进行处理，可以根据实际情况进行调整。