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=='''IPP Implementation Summary'''==
== '''TBB Implementation Summary''' ==
The TBB implementation was relatively simple, though not quite as simple as the OpenMP implementation. Instead of being able to simply use a #pragma to parallelize the code, we use the parallel_for functionality from TBB. We use the dimensions of the image to get the range, and then placed our functionality inside the lambda to be passed into the parallel_for call.
<syntaxhighlight>
void tbb_imgProcessor::saturateImg(cv::Mat& image, double saturationLvl) {
//supressing OpenCV messages
std::streambuf* coutbuf = std::cout.rdbuf();
std::cout.rdbuf(nullptr);
//HSV stands for hue saturation value
cv::Mat hsv;
cv::cvtColor(image, hsv, cv::COLOR_BGR2HSV);
//Set blocked range from the first entry to the last
tbb::parallel_for(tbb::blocked_range<int>(0, hsv.rows), [&](const tbb::blocked_range<int>& r) {
for (int y = r.begin(); y < r.end(); ++y)
{
for (int x = 0; x < hsv.cols; ++x)
{
// Get pixel value
cv::Vec3b color = hsv.at<cv::Vec3b>(cv::Point(x, y));
// Increase saturation by saturation Lvl color[1] is for saturation
color[1] = cv::saturate_cast<uchar>(color[1] * saturationLvl);
// Set pixel value
hsv.at<cv::Vec3b>(cv::Point(x, y)) = color;
}
}
});
//Convert image from HSV back to GBR
cv::cvtColor(hsv, image, cv::COLOR_HSV2BGR);
//stop supressing
std::cout.rdbuf(coutbuf);
}
void tbb_imgProcessor::brightenImg(cv::Mat& image, int brightnessLvl) {
//suppressing OpenCV messages
std::streambuf* coutbuf = std::cout.rdbuf();
std::cout.rdbuf(nullptr);
int width = image.cols;
int height = image.rows;
int channels = image.channels();
tbb::parallel_for(0, height, [&](int row) {
for (int col = 0; col < width; col++) {
for (int c = 0; c < channels; c++) {
uchar& pixel = image.at<cv::Vec3b>(row, col)[c];
pixel = cv::saturate_cast<uchar>(pixel + brightnessLvl);
}
}
});
//stop suppressing
std::cout.rdbuf(coutbuf);
}
void tbb_imgProcessor::sharpenImg(cv::Mat& image) {
//suppressing OpenCV messages
std::streambuf* coutbuf = std::cout.rdbuf();
std::cout.rdbuf(nullptr);
// Convert the image to grayscale
cv::Mat grayscale;
cv::cvtColor(image, grayscale, cv::COLOR_BGR2GRAY);
tbb::parallel_for(1, image.cols - 1, [&](int x) {
for (int y = 1; y < image.rows - 1; y++) {
double sum = 0.0;
for (int i = -1; i <= 1; i++) {
for (int j = -1; j <= 1; j++) {
sum += grayscale.at<uchar>(y + j, x + i) * LapKernel_[i + 1][j + 1];
}
}
for (int c = 0; c < 3; c++) {
image.at<cv::Vec3b>(y, x)[c] = cv::saturate_cast<uchar>(image.at<cv::Vec3b>(y, x)[c] + sum * .99);
}
}
});
//stop suppressing
std::cout.rdbuf(coutbuf);
}
</syntaxhighlight>
=='''Testing and Demonstration Program'''==
