Question

我想优化this代码，特别是此函数：

bool interpolate(const Mat &im, float ofsx, float ofsy, float a11, float a12, float a21, float a22, Mat &res)
{         
   bool ret = false;
   // input size (-1 for the safe bilinear interpolation)
   const int width = im.cols-1;
   const int height = im.rows-1;
   // output size
   const int halfWidth  = res.cols >> 1;
   const int halfHeight = res.rows >> 1;
   int dim = res.rows * res.cols;
   float *out = res.ptr<float>(0);
   for (int j=-halfHeight; j<=halfHeight; ++j)
   {
      const float rx = ofsx + j * a12;
      const float ry = ofsy + j * a22;
      #pragma omp simd
      for(int i=-halfWidth; i<=halfWidth; ++i)
      {
         float wx = rx + i * a11;
         float wy = ry + i * a21;
         const int x = (int) floor(wx);
         const int y = (int) floor(wy);
         if (x >= 0 && y >= 0 && x < width && y < height)
         {
            // compute weights
            wx -= x; wy -= y;
            // bilinear interpolation
            *out++ = 
               (1.0f - wy) * ((1.0f - wx) * im.at<float>(y,x)   + wx * im.at<float>(y,x+1)) +
               (       wy) * ((1.0f - wx) * im.at<float>(y+1,x) + wx * im.at<float>(y+1,x+1));
         } else {
            *out++ = 0;
            ret =  true; // touching boundary of the input            
         }
      }
   }
   return ret;
}

有人可以帮助在上面的代码中找到OpenCV中的等效函数吗？我不是图像处理的专家，所以我真的不知道上面的功能在细节上做了什么，但我认为这是一个扭曲仿射变换，即使我真的不知道如何定义一个OpenCV等价物。

输入图像似乎是模糊图像，原始图像或其小片。输出结果总是一个小补丁。

以下是一些示例：

示例1：

参数数量：

ofx=175.497 ofsy=315.06 a11=1.69477 a12=0.0671724 a21=0.0679493 a22=1.56309

输入图片：

输出图片：

示例2：

参数数量：

ofx=572.121 ofsy=326.659 a11=0.871508 a12=0 a21=0.346405 a22=1.14744

输入图片：

输出图片：

示例3：

ofx=66.571 ofsy=148.991 a11=1.12027 a12=0.126609 a21=0.126609 a22=2.53436

输入图片：

输出图片：

这些是调用函数的原始代码的不同部分：

  // warp input according to current shape matrix
  interpolate(wrapper.prevBlur, lx, ly, u11*ratio, u12*ratio, u21*ratio, u22*ratio, img);

  Mat smoothed(patchImageSize, patchImageSize, CV_32FC1, (void *)&workspace.front());
  // interpolate with det == 1
  if (!interpolate(img, x, y, a11, a12, a21, a22, smoothed))
  {

  // subsample with corresponding scale
  interpolate(smoothed, (float)(patchImageSize>>1), (float)(patchImageSize>>1), imageToPatchScale, 0, 0, imageToPatchScale, patch);


  // ok, do the interpolation
  interpolate(img, x, y, a11, a12, a21, a22, patch);

当我尝试以下列方式使用warpAffine时会发生这种情况：

  // warp input according to current shape matrix
  interpolate(wrapper.prevBlur, lx, ly, u11*ratio, u12*ratio, u21*ratio, u22*ratio, img);

  Mat warp_mat( 2, 3, CV_32FC1 );
  Mat myPatch(img.rows, img.cols, CV_32FC1);
  warp_mat.at<float>(0,2) = lx;
  warp_mat.at<float>(1,2) = ly;
  warp_mat.at<float>(0,0) = u11*ratio;
  warp_mat.at<float>(0,1) = u12*ratio;
  warp_mat.at<float>(1,0) = u21*ratio;
  warp_mat.at<float>(1,1) = u22*ratio;

  warpAffine(wrapper.prevBlur, myPatch, warp_mat, myPatch.size());

生成的myPatch矩阵是零矩阵，而img（由interpolate获得）是：

[19.109245, 19.189388, 18.941183, 18.454611, 18.285404, 19.447983, 22.037096, 28.504759, 37.753605, 50.69936, 61.34388, 67.619637, 70.699326, 71.640556, 73.347702, 72.383781, 70.7649, 72.320709, 74.32235;
 18.464636, 18.408369, 18.347059, 18.194805, 17.982847, 18.312258, 18.990305, 21.852564, 26.399525, 35.10569, 44.444019, 53.986103, 59.851856, 63.937149, 67.766968, 70.979973, 73.074722, 77.097763, 82.344398;
 17.838448, 17.706562, 17.580456, 17.869242, 18.216852, 18.72654, 19.004158, 20.150208, 21.66539, 26.167187, 31.805283, 41.04277, 48.207466, 54.719109, 59.793156, 65.378006, 71.004974, 77.016037, 86.317352;
 17.257101, 17.117496, 16.95055, 17.34347, 18.505379, 20.129673, 21.161978, 22.195414, 22.287436, 24.150574, 26.179817, 32.619934, 39.298115, 46.696926, 52.091522, 57.986988, 64.629898, 72.434052, 82.955505;
 16.810595, 16.665813, 16.672272, 17.16098, 18.665346, 21.783976, 24.785789, 27.150511, 27.23918, 27.834826, 27.594404, 30.645121, 35.405987, 42.133587, 46.915634, 51.880707, 57.028702, 64.57579, 74.402069;
 16.687065, 16.451401, 16.626608, 17.460049, 19.36956, 23.552647, 28.802736, 33.788773, 35.505379, 35.85894, 34.729523, 34.880505, 37.088661, 42.075432, 45.702, 49.056709, 51.509052, 56.637093, 63.660839;
 16.802176, 16.594761, 16.863697, 18.126085, 20.491119, 25.517574, 32.737259, 40.572498, 45.324429, 46.528313, 45.586109, 44.153858, 43.667118, 46.450905, 48.539593, 50.182858, 50.18359, 51.575584, 54.267056;
 17.036257, 17.025221, 17.271259, 18.925261, 22.124079, 27.620583, 35.921772, 46.177872, 54.232437, 57.583233, 57.648571, 55.857315, 53.885891, 54.148857, 55.00872, 54.9893, 52.946201, 50.873283, 49.034798;
 17.337849, 17.61212, 18.028404, 19.572941, 23.455297, 29.841951, 38.668663, 49.819805, 60.617371, 66.327873, 68.025574, 66.935631, 64.995117, 63.513988, 63.28405, 62.325748, 58.940784, 53.796066, 48.033508;
 17.798275, 18.203262, 19.018663, 20.718761, 24.611408, 31.378065, 40.706932, 51.637016, 63.323963, 71.373169, 74.578476, 74.412659, 74.106857, 72.411026, 71.710922, 70.007111, 66.181709, 58.721882, 50.149853;
 18.593805, 19.017687, 20.172789, 22.093014, 25.971659, 32.813194, 41.989246, 52.252911, 62.929924, 71.418938, 76.355003, 77.044289, 78.709656, 78.83432, 78.581551, 76.614075, 72.71788, 63.598377, 52.698578;
 19.567734, 20.197411, 21.640959, 24.039509, 27.603041, 34.091061, 42.821777, 52.127884, 61.030842, 68.610733, 73.860558, 75.530617, 78.25412, 81.30085, 82.840904, 80.822067, 76.685196, 67.430412, 54.54921;
 21.115396, 21.835562, 23.40497, 26.244884, 30.036913, 35.568745, 43.308716, 51.656746, 58.69318, 64.595673, 69.845467, 72.11985, 74.878944, 79.890228, 83.964821, 82.866249, 77.71666, 68.196243, 55.256557;
 23.264105, 24.024746, 25.705564, 28.513554, 32.514004, 37.26601, 43.47644, 50.611153, 56.786697, 61.13575, 66.052094, 69.762238, 71.692001, 76.810669, 81.848129, 82.157066, 76.844963, 66.500725, 54.042095;
 26.102678, 26.758638, 28.201065, 30.806498, 34.584103, 38.752495, 43.416939, 48.890656, 54.433743, 58.482693, 63.515507, 69.373245, 71.917755, 74.965172, 78.791039, 79.034378, 73.354454, 62.917992, 50.983219;
 29.008026, 30.016344, 30.787025, 32.692429, 35.850079, 39.365425, 42.956245, 46.993965, 51.688225, 56.120068, 61.624519, 69.804024, 74.923134, 76.170395, 76.252747, 74.715118, 68.599701, 58.000847, 47.082359;
 31.630077, 33.315144, 33.247631, 33.903202, 36.094364, 38.939133, 42.000217, 45.338474, 49.197887, 53.639317, 59.658398, 69.140472, 77.870468, 79.725624, 75.932251, 69.885872, 62.522583, 52.486378, 42.571148;
 34.113537, 36.435402, 35.544792, 34.225368, 35.189747, 37.445477, 40.579632, 44.427345, 48.191299, 52.085419, 57.660496, 66.887024, 77.807755, 81.70005, 76.676743, 66.486168, 56.192219, 46.825108, 38.276539;
 37.42725, 39.82682, 37.698589, 34.016525, 33.155304, 35.16758, 39.039139, 44.336964, 49.359722, 52.590809, 56.610603, 64.08419, 74.419289, 80.603294, 76.006302, 63.653465, 50.843102, 41.247444, 34.471062]

评论后更新：

这些是使用[[1, 0, 0], [0, 1, 0]]并使用以下代码的结果：

  Mat warp_mat( 2, 3, CV_32FC1 );
  Mat myPatch(img.rows, img.cols, CV_32FC1);
  warp_mat.at<float>(0,0) = 1;                  //u11*ratio
  warp_mat.at<float>(0,1) = 0;                  //u12*ratio
  warp_mat.at<float>(0,2) = 0+(img.cols >> 1);  //lx
  warp_mat.at<float>(1,0) = 0;                  //u21*ratio
  warp_mat.at<float>(1,1) = 1;                  //u22*ratio
  warp_mat.at<float>(1,2) = 0+(img.rows >> 1);  //ly

  warpAffine(wrapper.prevBlur, myPatch, warp_mat, myPatch.size());

  interpolate(wrapper.prevBlur, 0, 0, 1, 0, 0, 1, img);

  std::cout<<"img="<<std::endl<<img<<std::endl;
  std::cout<<"myPatch="<<std::endl<<myPatch<<std::endl;

结果是一样的，但如果我尝试使用：

  warp_mat.at<float>(0,0) = 1;                  //u11*ratio
  warp_mat.at<float>(0,1) = 1;                  //u12*ratio
  warp_mat.at<float>(0,2) = 0+(img.cols >> 1);  //lx
  warp_mat.at<float>(1,0) = 0;                  //u21*ratio
  warp_mat.at<float>(1,1) = 1;                  //u22*ratio
  warp_mat.at<float>(1,2) = 0+(img.rows >> 1);  //ly

  warpAffine(wrapper.prevBlur, myPatch, warp_mat, myPatch.size());

  interpolate(wrapper.prevBlur, 0, 0, 1, 1, 0, 1, img);

矩阵是“镜像的”：

myPatch=
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.4431293, 2.1086276, 1.7749974, 1.5721301, 1.5403291, 1.6410155, 1.8406107, 2.1113796, 2.3246853, 2.274801;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.3276107, 2.0702307, 1.8100098, 1.6615094, 1.6572961, 1.7410251, 1.8701531, 2.0462515, 2.1933937;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.3676813, 2.1666555, 1.9666147, 1.8710723, 1.9005303, 1.9753534, 2.0355756, 2.1005828;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.4378726, 2.2967758, 2.1802788, 2.1628339, 2.2288194, 2.2786529, 2.2584724;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.3656359, 2.3085568, 2.3188434, 2.4140301, 2.513881, 2.5077794;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.206573, 2.20857, 2.3185263, 2.5056028, 2.6312659;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.1686711, 2.1401191, 2.2343175, 2.4260342;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.3495517, 2.2178252, 2.1930335;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.6443374, 2.4216607;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.8480706]
img=
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.4431293, 2.1086276, 1.7749974, 1.5721301, 1.5403291, 1.6410155, 1.8406107, 2.1113796, 2.3246853, 2.274801;
 0, 0, 0, 0, 0, 0, 0, 0, 2.3276107, 2.0702307, 1.8100098, 1.6615094, 1.6572961, 1.7410251, 1.8701531, 2.0462515, 2.1933937, 2.1447542, 1.8548106;
 0, 0, 0, 0, 0, 0, 0, 2.3676813, 2.1666555, 1.9666147, 1.8710723, 1.9005303, 1.9753534, 2.0355756, 2.1005828, 2.1541297, 2.0949042, 1.8804716, 1.6108752;
 0, 0, 0, 0, 0, 0, 2.4378726, 2.2967758, 2.1802788, 2.1628339, 2.2288194, 2.2786529, 2.2584724, 2.2164674, 2.1899939, 2.1344388, 2.0028977, 1.8055484, 1.6097167;
 0, 0, 0, 0, 0, 2.3656359, 2.3085568, 2.3188434, 2.4140301, 2.513881, 2.5077794, 2.3889487, 2.2654738, 2.21731, 2.2129889, 2.1711345, 2.027447, 1.7903067, 1.5879864;
 0, 0, 0, 0, 2.206573, 2.20857, 2.3185263, 2.5056028, 2.6312659, 2.5770819, 2.3866575, 2.2314539, 2.2230167, 2.3092971, 2.3504019, 2.2321868, 1.9485472, 1.637617, 1.494508;
 0, 0, 0, 2.1686711, 2.1401191, 2.2343175, 2.4260342, 2.566293, 2.5228219, 2.3388758, 2.2057574, 2.2558136, 2.4211838, 2.5120842, 2.3888607, 2.0588915, 1.6645602, 1.4044838, 1.4204007;
 0, 0, 2.3495517, 2.2178252, 2.1930335, 2.3035395, 2.4375367, 2.446404, 2.3236551, 2.2328601, 2.3145993, 2.5046468, 2.5949829, 2.4436085, 2.0789487, 1.6472976, 1.3386253, 1.3225981, 1.6233296;
 0, 2.6443374, 2.4216607, 2.271126, 2.2733064, 2.367074, 2.4035037, 2.3307135, 2.2715025, 2.3534446, 2.5142543, 2.558598, 2.3710468, 2.0039113, 1.6069642, 1.3526549, 1.3859948, 1.7268054, 2.1843567;
 2.8480706, 2.6081781, 2.4022317, 2.3262172, 2.3576505, 2.3759208, 2.3233094, 2.2885542, 2.3600159, 2.4632583, 2.4390275, 2.2265964, 1.9053584, 1.6181513, 1.4964664, 1.6123655, 1.9332824, 2.2962041, 2.4815767]

最后使用：

  warp_mat.at<float>(0,0) = 0;                  //u11*ratio
  warp_mat.at<float>(0,1) = 1;                  //u22*ratio
  warp_mat.at<float>(0,2) = 0+(img.cols >> 1);  //lx
  warp_mat.at<float>(1,0) = 1;                  //u21*ratio
  warp_mat.at<float>(1,1) = 1;                  //u22*ratio
  warp_mat.at<float>(1,2) = 0+(img.rows >> 1);  //ly

我明白了：

myPatch=
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.4431293, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.1086276, 2.3276107, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.7749974, 2.0702307, 2.3676813, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.5721301, 1.8100098, 2.1666555, 2.4378726, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.5403291, 1.6615094, 1.9666147, 2.2967758, 2.3656359, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6410155, 1.6572961, 1.8710723, 2.1802788, 2.3085568, 2.206573, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.8406107, 1.7410251, 1.9005303, 2.1628339, 2.3188434, 2.20857, 2.1686711, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.1113796, 1.8701531, 1.9753534, 2.2288194, 2.4140301, 2.3185263, 2.1401191, 2.3495517, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.3246853, 2.0462515, 2.0355756, 2.2786529, 2.513881, 2.5056028, 2.2343175, 2.2178252, 2.6443374, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.274801, 2.1933937, 2.1005828, 2.2584724, 2.5077794, 2.6312659, 2.4260342, 2.1930335, 2.4216607, 2.8480706]
img=
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.4431293, 2.3276107, 2.3676813, 2.4378726, 2.3656359, 2.206573, 2.1686711, 2.3495517, 2.6443374, 2.8480706;
 0, 0, 0, 0, 0, 0, 0, 0, 2.1086276, 2.0702307, 2.1666555, 2.2967758, 2.3085568, 2.20857, 2.1401191, 2.2178252, 2.4216607, 2.6081781, 2.6495261;
 0, 0, 0, 0, 0, 0, 0, 1.7749974, 1.8100098, 1.9666147, 2.1802788, 2.3188434, 2.3185263, 2.2343175, 2.1930335, 2.271126, 2.4022317, 2.4685297, 2.4485474;
 0, 0, 0, 0, 0, 0, 1.5721301, 1.6615094, 1.8710723, 2.1628339, 2.4140301, 2.5056028, 2.4260342, 2.3035395, 2.2733064, 2.3262172, 2.3705757, 2.3652363, 2.3247712;
 0, 0, 0, 0, 0, 1.5403291, 1.6572961, 1.9005303, 2.2288194, 2.513881, 2.6312659, 2.566293, 2.4375367, 2.367074, 2.3576505, 2.3551981, 2.3311026, 2.2715149, 2.1814501;
 0, 0, 0, 0, 1.6410155, 1.7410251, 1.9753534, 2.2786529, 2.5077794, 2.5770819, 2.5228219, 2.446404, 2.4035037, 2.3759208, 2.3474753, 2.3124287, 2.240618, 2.1282687, 2.0381868;
 0, 0, 0, 1.8406107, 1.8701531, 2.0355756, 2.2584724, 2.3889487, 2.3866575, 2.3388758, 2.3236551, 2.3307135, 2.3233094, 2.3084226, 2.2854021, 2.2117574, 2.088321, 1.9926676, 1.9839712;
 0, 0, 2.1113796, 2.0462515, 2.1005828, 2.2164674, 2.2654738, 2.2314539, 2.2057574, 2.2328601, 2.2715025, 2.2885542, 2.2938819, 2.2722201, 2.1820612, 2.0477793, 1.957217, 1.954851, 2.0058911;
 0, 2.3246853, 2.1933937, 2.1541297, 2.1899939, 2.21731, 2.2230167, 2.2558136, 2.3145993, 2.3534446, 2.3600159, 2.3450513, 2.2874477, 2.1686828, 2.0435023, 1.9943975, 2.0270162, 2.0777535, 2.1049571;
 2.274801, 2.1447542, 2.0949042, 2.1344388, 2.2129889, 2.3092971, 2.4211838, 2.5046468, 2.5142543, 2.4632583, 2.3841665, 2.2811179, 2.1669631, 2.1026075, 2.1358697, 2.2212756, 2.2625117, 2.2268343, 2.180846]

Answer 1

我认为你基本上回答了自己，看起来像是一个基本的仿射变换。

OpenCV中的平等对象为warpAffine。在函数的flags中，您可以为其提供任何InterpolationFlags。

您的情况下的转换矩阵M将是：

[[a11, a12, ofsx],
 [a21, a22, ofsy]

输出大小也是一个参数，取决于您的数字。

如果您想按照自己的意愿进行优化，可以使用CUDA支持编译OpenCV，然后就可以使用此功能的GPU版本。

如何使用OpenCV编写此插值函数？

1 个答案: