How can I turn a three channel Mat into a summed up one channel Mat? - c++

Question

I want to add up all channels of a Mat image to a Mat image with only one sum-channel. I've tried it this way:
// sum up the channels of the image:
// 1 .store initial nr of rows/columns
int initialRows = frameVid1.rows;
int initialCols = frameVid1.cols;
// 2. check if matrix is continous
if (!frameVid1.isContinuous())
{
frameVid1 = frameVid1.clone();
}
// 3. reshape matrix to 3 color vectors
frameVid1 = frameVid1.reshape(3, initialRows*initialCols);
// 4. convert matrix to store bigger values than 255
frameVid1.convertTo(frameVid1, CV_32F);
// 5. sum up the three color vectors
reduce(frameVid1, frameVid1, 1, CV_REDUCE_SUM);
// 6. reshape to initial size
frameVid1 = frameVid1.reshape(1, initialRows);
// 7. convert back to CV_8UC1
frameVid1.convertTo(frameVid1, CV_8U);
But somehow reduce does not touch the color channels as a Matrix Dimension. Is there another function that can sum them up?
Also why does using CV_16U in step 4.) not work? (I had to put a CV_32F in there)
Thanks in advance!

Answer 1

You can sum the RGB channels with a single line
cv::transform(frameVid1, frameVidSum, cv::Matx13f(1,1,1))
You may need one more line, as before applying the transform you shall convert the image to some appropriate type to avoid saturation (I assumed CV_32FC3). -Output array is of the same size and depth as source.
Some explanation:
cv::transform may operate on per-pixel channel values.
Having the third argument cv::Matx13f(a, b, c) for each pixel [u,v] it does the following:
frameVidSum[u,v] = frameVid1[u,v].B * a + frameVid1[u,v].G * b + frameVid1[u,v].R * c
By using third argument cv::Matx13f(1,0,1) you will sum only blue and red channels.
cv::transform is so clever, you can even use cv::Matx14f and then the fourth value will be added (offset) to each pixel in the frameVidSum.

Answer 2

Every 3rd element (in RGB) is one similar colour. Probably it will work if you grab every group of 3 elements (R, G and B) sum them up and store it in another 1-channel matrix. Before storing you should use saturate cast to avoid unexpected results. So, I think the better way is to use saturate cast instead of adapting your matrix.

Answer 3

Have a look at cv::split() and cv::add() functions.
You can use the split function to split the image into separate channels and then the add function to add the images. But be careful when using add because adding may lead to saturation of values. You may have to first convert types and then add. Have a look here: http://answers.opencv.org/question/13769/adding-matrices-without-saturation/