OpenCV源码系列|图像反模糊

#include <iostream>
#include <opencv2/opencv.hpp>
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
using namespace cv;
using namespace std;

void calcPSF(Mat& outputImg, Size filterSize, int len, double theta);
void fftshift(const Mat& inputImg, Mat& outputImg);
void filter2DFreq(const Mat& inputImg, Mat& outputImg, const Mat& H);
void calcWnrFilter(const Mat& input_h_PSF, Mat& output_G, double nsr);
void edgetaper(const Mat& inputImg, Mat& outputImg, double gamma = 5.0, double beta = 0.2);
int adjust_len = 10;
void adjust_filter(int, void*);
int  THETA =53;
int snr = 5200;//SNR表示信噪比

Mat src = imread("original.jpg", IMREAD_GRAYSCALE);
int main(int argc, char *argv[])
{
    if (src.empty()) 
    {
        printf("ERROR : Image cannot be loaded..!!");
        return -1;
    }
    imshow("input", src);
    namedWindow("result", WINDOW_AUTOSIZE);
    createTrackbar("Adjust R:", "result", &adjust_len, 60, adjust_filter);
    createTrackbar("THETA:", "result", &THETA, 360, adjust_filter);
   createTrackbar("snr:", "result", &snr, 10000,adjust_filter);

    Mat imgOut;
    Rect roi = Rect(0, 0, src.cols & -2, src.rows & -2);
    Mat Hw, h;
    calcPSF(h, roi.size(), adjust_len, THETA);
    calcWnrFilter(h, Hw, 1.0 / double(snr));

    src.convertTo(src, CV_32F);
    edgetaper(src, src);

    filter2DFreq(src(roi), imgOut, Hw);

    imgOut.convertTo(imgOut, CV_8U);
    normalize(imgOut, imgOut, 0, 255, NORM_MINMAX);
    imwrite("motion_deblur_result.jpg", imgOut);
    imshow("result", imgOut);
    waitKey(0);
    return 0;
}
//
void adjust_filter(int, void*) {

    Mat imgOut;
    ////偶数处理
    Rect roi = Rect(0, 0, src.cols & -2, src.rows & -2);
    Mat Hw, h;

    //生成PSF与维纳滤波器 
    calcPSF(h, roi.size(), adjust_len, THETA);
    calcWnrFilter(h, Hw, 1.0 / double(snr));

    src.convertTo(src, CV_32F);
    edgetaper(src, src);
    //反模糊 
    filter2DFreq(src(roi), imgOut, Hw);

     //归一化显示 
    imgOut.convertTo(imgOut, CV_8U);
    normalize(imgOut, imgOut, 0, 255, NORM_MINMAX);
    imwrite("motion_deblur_result.jpg", imgOut);
    imshow("result", imgOut);
}

//计算PSF
//https://blog.csdn.net/qq254612999/article/details/50509793
void calcPSF(Mat& outputImg, Size filterSize, int len, double theta)
{
    Mat h(filterSize, CV_32F, Scalar(0));
    Point point(filterSize.width / 2, filterSize.height / 2);
    ellipse(h, point, Size(0, cvRound(float(len) / 2.0)), 90.0 - theta, 0, 360, Scalar(255), FILLED);
    Scalar summa = sum(h);
    outputImg = h / summa[0];
}

//图像傅里叶变换
//https://www.jianshu.com/p/89ce7fdb9e12
void fftshift(const Mat& inputImg, Mat& outputImg)
{
    outputImg = inputImg.clone();
    int cx = outputImg.cols / 2;
    int cy = outputImg.rows / 2;
    Mat q0(outputImg, Rect(0, 0, cx, cy));
    Mat q1(outputImg, Rect(cx, 0, cx, cy));
    Mat q2(outputImg, Rect(0, cy, cx, cy));
    Mat q3(outputImg, Rect(cx, cy, cx, cy));
    Mat tmp;
    q0.copyTo(tmp);
    q3.copyTo(q0);
    tmp.copyTo(q3);
    q1.copyTo(tmp);
    q2.copyTo(q1);
    tmp.copyTo(q2);
}

//实现反模糊
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);
    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;
    mulSpectrums(complexI, complexH, complexIH, 0);
    idft(complexIH, complexIH);
    split(complexIH, planes);
    outputImg = planes[0];
}

//生成维纳滤波算法
//https://wenku.baidu.com/view/76bd5f36f111f18583d05a00.html
void calcWnrFilter(const Mat& input_h_PSF, Mat& output_G, double nsr)
{
    Mat h_PSF_shifted;
    fftshift(input_h_PSF, h_PSF_shifted);
    Mat planes[2] = { Mat_<float>(h_PSF_shifted.clone()), Mat::zeros(h_PSF_shifted.size(), CV_32F) };
    Mat complexI;
    merge(planes, 2, complexI);
    dft(complexI, complexI);
    split(complexI, planes);
    Mat denom;
    pow(abs(planes[0]), 2, denom);
    denom += nsr;
    divide(planes[0], denom, output_G);
}

void edgetaper(const Mat& inputImg, Mat& outputImg, double gamma, double beta)
{
    int Nx = inputImg.cols;
    int Ny = inputImg.rows;
    Mat w1(1, Nx, CV_32F, Scalar(0));
    Mat w2(Ny, 1, CV_32F, Scalar(0));
    float* p1 = w1.ptr<float>(0);
    float* p2 = w2.ptr<float>(0);
    float dx = float(2.0 * CV_PI / Nx);
    float x = float(-CV_PI);
    for (int i = 0; i < Nx; i++)
    {
        p1[i] = float(0.5 * (tanh((x + gamma / 2) / beta) - tanh((x - gamma / 2) / beta)));
        x += dx;
    }
    float dy = float(2.0 * CV_PI / Ny);
    float y = float(-CV_PI);
    for (int i = 0; i < Ny; i++)
    {
        p2[i] = float(0.5 * (tanh((y + gamma / 2) / beta) - tanh((y - gamma / 2) / beta)));
        y += dy;
    }
    Mat w = w2 * w1;
    multiply(inputImg, w, outputImg);
}