OpenCV : homomorphic filter

Question

i want to use a homomorphic filter to work on underwater image. I tried to code it with the codes found on the internet but i have always a black image... I tried to normali

Answer 1

I was doing this method to balance illumination when camera was changed caused the Image waw dark!

I tried to FFT to the frequency to filter the image! it's work.but use too much time.(2750*3680RGB image).so I do it in Spatial domain.

here is my code!

//IplImage *imgSrcI=cvLoadImage("E:\\lean.jpg",-1);
Mat imgSrcM(imgSrc,true);
Mat imgDstM;

Mat imgGray;
Mat imgHls;
vector<Mat> vHls;

Mat imgTemp1=Mat::zeros(imgSrcM.size(),CV_64FC1);
Mat imgTemp2=Mat::zeros(imgSrcM.size(),CV_64FC1);

if(imgSrcM.channels()==1)
{
    imgGray=imgSrcM.clone();
}
else if (imgSrcM.channels()==3)
{
    cvtColor(imgSrcM, imgHls, CV_BGR2HLS);
    split(imgHls, vHls);
    imgGray=vHls.at(1);
}
else
{
    return -1;
}
imgGray.convertTo(imgTemp1,CV_64FC1);
imgTemp1=imgTemp1+0.0001;
log(imgTemp1,imgTemp1);

GaussianBlur(imgTemp1, imgTemp2, Size(21, 21), 0.1, 0.1, BORDER_DEFAULT);//imgTemp2是低通滤波的结果
imgTemp1 = (imgTemp1 - imgTemp2);//imgTemp1是对数减低通的高通
addWeighted(imgTemp2, 0.7, imgTemp1, 1.4, 1, imgTemp1, -1);//imgTemp1是压制低频增强高频的结构

exp(imgTemp1,imgTemp1);
normalize(imgTemp1,imgTemp1,0,1,NORM_MINMAX);
imgTemp1=imgTemp1*255;

imgTemp1.convertTo(imgGray, CV_8UC1);

//imwrite("E:\\leanImgGray.jpg",imgGray);
if (imgSrcM.channels()==3)
{
    vHls.at(1)=imgGray;
    merge(vHls,imgHls);
    cvtColor(imgHls, imgDstM, CV_HLS2BGR);

}
else if (imgSrcM.channels()==1)
{
    imgDstM=imgGray.clone();
}

cvCopy(&(IplImage)imgDstM,imgDst);
//cvShowImage("jpg",imgDst);

return 0;

Answer 2

I took your code corrected it at a few places and got decent results as the homographic filter output.

Here are the corrections that I made.

1) Instead of working just on the image_mag, work on the full output of the FFT.

2) your filter values of high_h_v_TB = 101 and low_h_v_TB = 99 virtually made little effect in filtering.

Here are the values I used.

int high_h_v_TB = 100;
int low_h_v_TB = 20;
int D = 10;// radius of band pass filter parameter
int order = 4;

Here is my main code

//float_img == grayscale image in 0-1 scale
Mat log_img;
log(float_img, log_img);


Mat fft_phase, fft_mag;
Mat fft_complex;
HomomorphicFilter::Fourier_Transform(log_img, fft_complex);
HomomorphicFilter::ShiftFFT(fft_complex);

int high_h_v_TB = 100;
int low_h_v_TB = 30;
int D = 10;// radius of band pass filter parameter
int order = 4;

//get a butterworth filter of same image size as the input image
//dont call mulSpectrums yet, just get the filter of correct size
Mat butterWorthFreqDomain;
HomomorphicFilter::ButterworthFilter(fft_complex.size(), butterWorthFreqDomain,  D, order, high_h_v_TB, low_h_v_TB);


//this should match fft_complex in size and type
//and is what we will be using for 'mulSpectrums' call
Mat butterworth_complex;
//make two channels to match fft_complex
Mat butterworth_channels[] = {Mat_<float>(butterWorthFreqDomain.size()), Mat::zeros(butterWorthFreqDomain.size(), CV_32F)};
merge(butterworth_channels, 2, butterworth_complex);


//do mulSpectrums on the full fft
mulSpectrums(fft_complex, butterworth_complex, fft_complex, 0);

//shift back the output
HomomorphicFilter::ShiftFFT(fft_complex);
Mat log_img_out;

HomomorphicFilter::Inv_Fourier_Transform(fft_complex,  log_img_out);

Mat float_img_out;
exp(log_img_out, float_img_out);
//float_img_out is gray in 0-1 range

Here is my output.