2、双线性：由相邻的四像素(2*2)计算得出，公式，
- uchar* dataDst = matDst1.data;
- int stepDst = matDst1.step;
- uchar* dataSrc = matSrc.data;
- int stepSrc = matSrc.step;
- int iWidthSrc = matSrc.cols;
- int iHiehgtSrc = matSrc.rows;
- for (int j = 0; j < matDst1.rows; ++j)
- {
- float fy = (float)((j + 0.5) * scale_y - 0.5);
- int sy = cvFloor(fy);
- fy -= sy;
- sy = std::min(sy, iHiehgtSrc - 2);
- sy = std::max(0, sy);
- short cbufy[2];
- cbufy[0] = cv::saturate_cast<short>((1.f - fy) * 2048);
- cbufy[1] = 2048 - cbufy[0];
- for (int i = 0; i < matDst1.cols; ++i)
- {
- float fx = (float)((i + 0.5) * scale_x - 0.5);
- int sx = cvFloor(fx);
- fx -= sx;
- if (sx < 0) {
- fx = 0, sx = 0;
- }
- if (sx >= iWidthSrc - 1) {
- fx = 0, sx = iWidthSrc - 2;
- }
- short cbufx[2];
- cbufx[0] = cv::saturate_cast<short>((1.f - fx) * 2048);
- cbufx[1] = 2048 - cbufx[0];
- for (int k = 0; k < matSrc.channels(); ++k)
- {
- *(dataDst+ j*stepDst + 3*i + k) = (*(dataSrc + sy*stepSrc + 3*sx + k) * cbufx[0] * cbufy[0] +
- *(dataSrc + (sy+1)*stepSrc + 3*sx + k) * cbufx[0] * cbufy[1] +
- *(dataSrc + sy*stepSrc + 3*(sx+1) + k) * cbufx[1] * cbufy[0] +
- *(dataSrc + (sy+1)*stepSrc + 3*(sx+1) + k) * cbufx[1] * cbufy[1]) >> 22;
- }
- }
- }
- cv::imwrite("linear_1.jpg", matDst1);
- cv::resize(matSrc, matDst2, matDst1.size(), 0, 0, 1);
- cv::imwrite("linear_2.jpg", matDst2);
