【OpenCV】图像清晰度评估

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#include <iostream>  
#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp> 
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur
#include <opencv2/ml/ml.hpp>
#include <opencv2/contrib/contrib.hpp>
#include "JPEGQ.h"

using namespace cv;
using namespace std;

Mat dojob(Mat &img);

int main()
{
	char filename[100];
	double threshold = 7.7;
	int num = 13;

	for (int a = 7; a < num; a++){
		sprintf(filename, "test2018/test%d.jpg", a);
		cout << a << "=================" << filename << endl;
		Mat x1 = imread(filename, IMREAD_GRAYSCALE);
		//imshow("image", x1);
		int M = x1.rows;
		int N = x1.cols;
		cout << "height :" << M << " " << " width :" << N << endl;
		//Mat x;
		//x1.convertTo(x, CV_64F);//转换成浮点运算

		//JPEGQ *jpegq = new JPEGQ();
		//jpegq->h_feature(x, M, N);
		//jpegq->v_feature(x, M, N);
		//jpegq->combine_feature();
		//double score = jpegq->qual_predict();

		//if (score<threshold){
		//	cout << "this is a blur image" << endl;
		//}

//		cout << "the image :" << k << " " << " score is :" << score << endl;


		Mat imm;
		x1.copyTo(imm);
		//imshow("w",imm);
		/*
		namedWindow("w1",WINDOW_AUTOSIZE);
		namedWindow("w",WINDOW_AUTOSIZE);
		namedWindow("w2",WINDOW_AUTOSIZE);
		namedWindow("w3",WINDOW_AUTOSIZE);
		*/
		Mat t1, t2, t3;
		t1 = dojob(x1);
		Mat t;
		Size s(t1.cols / 8, t1.rows / 8);
		resize(t1, t, s);
		imshow("t0", t);
		cout << "t height :" << t.cols << " " << " t width :" << t.rows << endl;
		//waitKey(0);
		int i, j, k, l;
		for (i = 0; i < t.cols; i++){
			for (j = 0; j<t.rows; j++){
				Point u, d;
				u.x = j; u.y = i;
				d.x = u.x + 7; d.y = u.y + 7;
				Rect R(u, d);
				Mat seg = t1(R);
				double p = 0, q = 0;
				minMaxLoc(seg, &p, &q);
				t.at<double>(Point(i, j)) = q;
			}
		}
		
		t.copyTo(t1);
		t2 = dojob(x1);
		Size s2(t2.cols / 4, t2.rows / 4);
		resize(t2, t, s2);
		for (i = 0; i<t.cols; i++)
			for (j = 0; j<t.rows; j++)
			{
				Point u, d;
				u.x = j; u.y = i;
				d.x = u.x + 3; d.y = u.y + 3;
				Rect R(u, d);
				Mat seg = t2(R);
				double p = 0, q = 0;
				minMaxLoc(seg, &p, &q);
				t.at<double>(Point(i, j)) = q;
			}
		t.copyTo(t2);

		t3 = dojob(x1);
		Size s3(t3.cols / 2, t3.rows / 2);
		resize(t3, t, s3);
		for (i = 0; i<t.cols; i++)
			for (j = 0; j<t.rows; j++)
			{
				Point u, d;
				u.x = j; u.y = i;
				d.x = u.x + 1; d.y = u.y + 1;
				Rect R(u, d);
				Mat seg = t3(R);
				double p = 0, q = 0;
				minMaxLoc(seg, &p, &q);
				t.at<double>(Point(i, j)) = q;
			}
		t.copyTo(t3);
		imshow("w1",t1);
		imshow("w2",t2);
		imshow("w3",t3);
		//waitKey(0);
		//Time to check
		//cout<<t1.rows<<" "<<t2.rows<<" "<<t3.rows<<endl;
		int da = 0, gr = 0, bl = 0;
		for (i = 0; i<t1.cols; i++)
			for (j = 0; j<t1.rows; j++)
			{
				double p, q, r;
				p = t1.at<double>(Point(i, j)) * 255;
				q = t2.at<double>(Point(i, j)) * 255;
				r = t3.at<double>(Point(i, j)) * 255;
				if (p<30 && q<30 && r<30) continue;
				//	cerr<<"Edge detected"<<endl;
				if (p>q && q>r)da++;
				if (p<q && q<r)gr++;
				if (q>p && q>r)gr++;
				if (p<q && 30>p)bl++;
			}
		//cerr<<da<<" "<<gr<<" "<<bl<<endl;
		double per = da; per /= (da + gr); per *= 100;
		double blur = bl; blur /= gr; blur *= 100;
		cout <<"========result : " << a << " per : " << per << " blur " << blur << endl;
		//waitKey(0);
	}

	waitKey(0);
	

	return 0;

}


Mat dojob(Mat &img)
{
	Mat r, c, d, b;
	b = (Mat_<double>(2, 2) <<
		1, 1, 1, 1);
	r = (Mat_<double>(2, 2) <<
		1, 1,
		-1, -1);
	c = (Mat_<double>(2, 2) <<
		1, -1,
		1, -1);
	d = (Mat_<double>(2, 2) <<
		1, -1,
		-1, 1);
	Mat row, col, dia, blu;
	Mat temp, ans;
	Size size(img.cols / 2, img.rows / 2);
	filter2D(img, temp, CV_64F, r);
	resize(temp, row, size);
	filter2D(img, temp, CV_64F, c);
	resize(temp, col, size);
	filter2D(img, temp, CV_64F, d);
	resize(temp, dia, size);
	Mat t, tt;
	multiply(row, row, t);
	t.copyTo(tt);
	multiply(col, col, t);
	tt += t;
	multiply(dia, dia, t);
	tt += t;
	sqrt(t, ans);
	normalize(ans, ans, 0, 1, NORM_MINMAX);
	filter2D(img, temp, CV_64F, b);
	resize(temp, blu, size);
	blu.copyTo(img);
	img /= 4;
	return ans;
}

图像评价指标

https://blog.csdn.net/purgle/article/details/73719101

http://sse.tongji.edu.cn/linzhang/IQA/IQA.htm

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