how can i removing sinusoidal noise w\ frequency domain in opencv - opencv

Question

i'm trying to remove '5 lines' in section, in music papers, my original image is this : http://en.wikipedia.org/wiki/Requiem_(Mozart)#/media/File:K626_Requiem_Mozart.jpg
First, i apply gaussian filter and binarized with threshold (min:100, max 255).
Then applying dft to this image, erase some appropriate lines, and reconstruct image by inverse dft.
i use sample code in opencv documentation, actually i doubt myself that i understand this code. :(
http://docs.opencv.org/doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.html
in this sample code, there's 2 Mats. one is 'complexI' for spectrum, another is 'magI' for actual visualized. the result of cv::dft is complexI, magI is normalized complexI. my question is this. how can i add a black line(to cancel in freq domain) and reconstruct?

Answer 1

OpenCV (now) provides a detailed tutorial on how to deal with periodic noise by spectral filtering: https://docs.opencv.org/trunk/d2/d0b/tutorial_periodic_noise_removing_filter.html
It hinges on using cv::dft(), cv::idft(), cv::mulSpectrums(), and cv::magnitude().
The core function (from the tutorial) to perform the filtering goes like so:
void filter2DFreq(const Mat& inputImg, Mat& outputImg, const Mat& H)
{
Mat planes[2] = { Mat_<float>(inputImg.clone()), Mat::zeros(inputImg.size(), CV_32F) };
Mat complexI;
merge(planes, 2, complexI);
// find FT of image
dft(complexI, complexI, DFT_SCALE);
Mat planesH[2] = { Mat_<float>(H.clone()), Mat::zeros(H.size(), CV_32F) };
Mat complexH;
merge(planesH, 2, complexH);
Mat complexIH;
// apply spectral filter
mulSpectrums(complexI, complexH, complexIH, 0);
// reconstruct the filtered image
idft(complexIH, complexIH);
split(complexIH, planes);
outputImg = planes[0];
}
Refer to the tutorial for more information.