# Implement Nearest Neighbour Interpolation using a Lookup Table?

Is it possible to use a Lookup Table to perform Nearest Neighbour Interpolation? I have implemented this algorithm using standard for loops. But I have heard using Lookup Tables are much more efficient.

*Note I am aware of cv::resize() that can perform Nearest Neighbour Interpolation. I implementing my own Nearest Neighbour Interpolation for learning.

My below code performs Nearest Neighbour Interpolation using for loops. How can I convert it to use a cv::LUT?

void nearest_neighbour_interpolation(const Mat& image, Mat& result, double scaleFactor)
{
// TODO: handle both 1 channel and 3 channel
// TODO: see if can use a LUT here

if (scaleFactor < 1.0000)
return;

int width = image.cols*scaleFactor;
int height = image.rows*scaleFactor;
result = Mat(height, width, image.type());

int x_ratio = (int)((image.cols << 16) / width) + 1;
int y_ratio = (int)((image.rows << 16) / height) + 1;

for (int c = 0; c < width; c++) {
for (int r = 0; r < height; r++) {

int imageC = ((c*x_ratio) >> 16); // c * scaleFactor?
int imageR = ((r*y_ratio) >> 16);
result.at<Vec3b>(Point(c, r)) = image.at<Vec3b>(Point(imageC, imageR));
}
}
}

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