OpenCV图像处理——修复失焦模糊的图像

前言

这是一个图像去模糊的小demo,用OpenCV实现。

代码:

#include 
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2\highgui.hpp"

using namespace cv;
using namespace std;

int r = 10;
int snr = 60;

void deblur(cv::Mat &src, cv::Mat &dst, int r, int snr);
void calcPSF(Mat& outputImg, Size filterSize, int R);
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);

int main(void)
{
     
	
	Mat src = imread("222.jpeg");
	namedWindow("原图", 0);
	cv::imshow("原图", src);
	cv::Mat dst;

	deblur(src, dst, r, snr);
	namedWindow("去模糊:", 0);
	imshow("去模糊:", dst);
	waitKey(0);
	return 0;
}

void deblur(cv::Mat &src, cv::Mat &dst, int r, int snr)
{
     
	cv::Mat gray;
	if (src.data == nullptr)
	{
     
		return;
	}
	if (src.channels() > 1)
	{
     
		cv::cvtColor(src, gray, CV_BGR2GRAY);
	}

	Rect roi = Rect(0, 0, gray.cols & -2, gray.rows & -2);

	Mat Hw, h;
	calcPSF(h, roi.size(), r);
	calcWnrFilter(h, Hw, 1.0 / double(snr));

	filter2DFreq(gray(roi), dst, Hw);

	dst.convertTo(dst, CV_8U);
	normalize(dst, dst, 0, 255, NORM_MINMAX);
}

void calcPSF(Mat& outputImg, Size filterSize, int R)
{
     
	Mat h(filterSize, CV_32F, Scalar(0));
	Point point(filterSize.width / 2, filterSize.height / 2);
	circle(h, point, R, 255, -1, 8);
	Scalar summa = sum(h);
	outputImg = h / summa[0];
}

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);
}

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];
}
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);
}

运行效果:
OpenCV图像处理——修复失焦模糊的图像_第1张图片

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