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→Box Blur on an image using opencv C++ Library (Max Fainshtein)
The application has the opportunity to receive an incredible boost to performance with the addition of parallel programming as most of the computational time is made up of calculating the average of every pixel which can be calculated concurrently, while only requiring a single synchronization at the end before we display the image.
=== Source Code for Box Blur ===
<syntaxhighlight lang="cpp">
int findingNeighbors(Mat img, int i, int j, int neighbour,float * b, float * g, float * r) {
int row_limit = img.rows;
int column_limit = img.cols;
Scalar temp;
double sum = 0, blue=0, red=0, green=0;
for (int x = i - floor(neighbour / 2); x <= i + floor(neighbour / 2); x++) {
for (int y = j - floor(neighbour / 2); y <= j + floor(neighbour / 2); y++) {
if (x >= 0 && y >= 0 && x < row_limit && y < column_limit) {
temp = img.at<Vec3b>(x, y);
blue += temp.val[0];
green += temp.val[1];
red += temp.val[2];
}
}
}
*b = blue / pow(neighbour, 2);
*g = green / pow(neighbour, 2);
*r = red / pow(neighbour, 2);
return 1;
}
</syntaxhighlight>
=== Algorithms (Joseph Pildush)===
<syntaxhighlight lang="cpp>
int iDevice;
}
dim3 blockDims(resident_threads/resident_blocks,1,1);
</syntaxhighlight>
