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opencv学习之路(20)、直方图应用

时间:2017-08-20 22:27:19      阅读:208      评论:0      收藏:0      [点我收藏+]

标签:har   const   read   point   pen   create   灰度   统计   class   

一、直方图均衡化--equalizeHist()

 1 #include "opencv2/opencv.hpp"
 2 using namespace cv;
 3 
 4 void main()
 5 {
 6     Mat srcImg = imread("E://02.jpg", 0);  //以灰度方式打开,需要输入单通道图像
 7     imshow("src", srcImg);
 8     Mat dstImg;  //均衡化后的图像
 9     equalizeHist(srcImg, dstImg);
10     imshow("dst", dstImg);
11 
12     //绘制src直方图
13     MatND dstHist;  //定义存储直方图变量
14     int dims = 1;  //需要统计的特征数目(只统计灰度值)
15     float hranges[] = {0, 256};  //范围[0,256)注意是最大值加1
16     const float* ranges[] = {hranges};
17     int bins = 256;
18     int channels = 0;
19     calcHist(&srcImg, 1, &channels, Mat(), dstHist, dims, &bins, ranges);
20     int scale = 1;
21     Mat HistImg(bins * scale, bins*1, CV_8UC3, Scalar(0));  //定义直方图输出图像
22     double minValue = 0;
23     double maxValue = 0;
24     minMaxLoc(dstHist, &minValue, &maxValue, 0, 0);
25     int hpt = saturate_cast<int>(0.9*bins);  //设置最大值并防止溢出
26     int j=0;
27     for(int i=0; i<256; i++)
28     {
29         float binValue = dstHist.at<float>(i);
30         int realValue = saturate_cast<int>(binValue*hpt/maxValue);  //归一化数据
31         line(HistImg, Point(i*scale, bins-1), Point(i*scale, bins-realValue), Scalar(0, 255, 0), 1, 8);
32     }
33     imshow("src_hist", HistImg);
34 
35     //绘制dst直方图
36     calcHist(&dstImg, 1, &channels, Mat(), dstHist, dims, &bins, ranges);
37     Mat HistImg2(bins * scale, bins*1, CV_8UC3, Scalar(0));  //定义直方图输出图像
38     for(int i=0; i<256; i++)
39     {
40         float binValue = dstHist.at<float>(i);
41         int realValue = saturate_cast<int>(binValue*hpt/maxValue);  //归一化数据
42         line(HistImg2, Point(i*scale, bins-1), Point(i*scale, bins-realValue), Scalar(0, 255, 0), 1, 8);
43     }
44     imshow("dst_hist", HistImg2);
45 
46     waitKey(0);
47 }

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注意:红色部分为均衡化的主要代码

彩色图像直方图均衡化

 1 #include "opencv2/opencv.hpp"
 2 using namespace cv;
 3 
 4 void main()
 5 {
 6     Mat src = imread("E://05.jpg"); 
 7     imshow("src", src);
 8 
 9     //分割通道
10     vector<Mat>channels;
11     split(src,channels);
12     Mat blue,green,red,dst;
13     blue=channels.at(0);
14     green=channels.at(1);
15     red=channels.at(2);
16     //分别对BGR通道做直方图均衡化
17     equalizeHist(blue,blue);
18     equalizeHist(green,green);
19     equalizeHist(red,red);
20     //合并通道
21     merge(channels,dst);
22     imshow("dst", dst);
23 
24     waitKey(0);
25 }

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二、直方图对比

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 1 #include "opencv2/opencv.hpp"
 2 #include<iostream>
 3 using namespace cv;
 4 using namespace std;
 5 
 6 void main()
 7 {
 8     Mat src1 = imread("E://a.jpg"); 
 9     Mat src2 = imread("E://b.jpg"); 
10     imshow("src1", src1);
11     imshow("src2", src2);
12 
13     MatND dstHist;  //定义存储直方图变量
14     int dims = 1;  //需要统计的特征数目(只统计灰度值)
15     float hranges[] = {0, 256};  //范围[0,256)注意是最大值加1
16     const float* ranges[] = {hranges};
17     int bins = 256;
18     int channels = 0;
19     calcHist(&src1, 1, &channels, Mat(), dstHist, dims, &bins, ranges);
20     int scale = 1;
21     Mat HistImg(bins * scale, bins*1, CV_8UC3, Scalar(0));  //定义直方图输出图像
22     double minValue = 0;
23     double maxValue = 0;
24     minMaxLoc(dstHist, &minValue, &maxValue, 0, 0);
25     int hpt = saturate_cast<int>(0.9*bins);  //设置最大值并防止溢出
26     int j=0;
27     for(int i=0; i<256; i++)
28     {
29         float binValue = dstHist.at<float>(i);
30         int realValue = saturate_cast<int>(binValue*hpt/maxValue);  //归一化数据
31         line(HistImg, Point(i*scale, bins-1), Point(i*scale, bins-realValue), Scalar(0, 255, 0), 1, 8);
32     }
33     imshow("src1_hist", HistImg);
34 
35     MatND dstHist2;  //定义存储直方图变量
36     calcHist(&src2, 1, &channels, Mat(), dstHist2, dims, &bins, ranges);
37     Mat HistImg2(bins * scale, bins*1, CV_8UC3, Scalar(0));  //定义直方图输出图像
38     minMaxLoc(dstHist2, &minValue, &maxValue, 0, 0);
39     for(int i=0; i<256; i++)
40     {
41         float binValue = dstHist2.at<float>(i);
42         int realValue = saturate_cast<int>(binValue*hpt/maxValue);  //归一化数据
43         line(HistImg2, Point(i*scale, bins-1), Point(i*scale, bins-realValue), Scalar(0, 255, 0), 1, 8);
44     }
45     imshow("src2_hist", HistImg2);
46 
47     double matchValue0 = compareHist(dstHist, dstHist2, CV_COMP_CORREL);  //值越大相似度越高
48     double matchValue1 = compareHist(dstHist, dstHist2, CV_COMP_CHISQR);  //值越小相似度越高
49     double matchValue2 = compareHist(dstHist, dstHist2, CV_COMP_INTERSECT); //值越大相似度越高
50     double matchValue3 = compareHist(dstHist, dstHist2, CV_COMP_BHATTACHARYYA); //值越小相似度越高
51 
52     cout<<"matchValue0(max_best)="<<matchValue0<<endl;
53     cout<<"matchValue1(min_best)="<<matchValue1<<endl;
54     cout<<"matchValue2(max_best)="<<matchValue2<<endl;
55     cout<<"matchValue3(min_best)="<<matchValue3<<endl;
56 
57     waitKey(0);
58 }

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三、反向投影

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 1 #include "opencv2/opencv.hpp"
 2 using namespace cv;
 3 
 4 #define WINDOW_NAME "【原始图】" 
 5 Mat g_hueImage;
 6 int g_bins = 30;//直方图组距
 7 
 8 void on_BinChange(int, void* )
 9 {
10     MatND hist;
11     int histSize = MAX( g_bins, 2 );
12     float hue_range[] = { 0, 180 };
13     const float* ranges = { hue_range };
14     calcHist( &g_hueImage, 1, 0, Mat(), hist, 1, &histSize, &ranges, true, false );
15     normalize( hist, hist, 0, 255, NORM_MINMAX, -1, Mat() );
16 
17     MatND backproj;
18     calcBackProject( &g_hueImage, 1, 0, hist, backproj, &ranges, 1, true );
19     imshow( "反向投影图", backproj );
20 
21     int w = 400; int h = 400;
22     int bin_w = cvRound( (double) w / histSize );
23     Mat histImg = Mat::zeros( w, h, CV_8UC3 );
24     for( int i = 0; i < g_bins; i ++ )
25     { 
26         rectangle( histImg, Point( i*bin_w, h ), Point( (i+1)*bin_w, h - cvRound( hist.at<float>(i)*h/255.0 ) ), Scalar( 100, 123, 255 ), -1 ); 
27     }
28     imshow( "直方图", histImg );
29 }
30 
31 void main()
32 {
33     Mat g_srcImage = imread( "E://1.jpg" );
34     Mat g_hsvImage;
35     resize(g_srcImage, g_srcImage, Size(g_srcImage.cols/4, g_srcImage.rows/4));//原图太大,进行缩放
36     cvtColor( g_srcImage, g_hsvImage, CV_BGR2HSV );
37 
38     g_hueImage.create( g_hsvImage.size(), g_hsvImage.depth() );
39     int ch[ ] = { 0, 0 };
40     mixChannels( &g_hsvImage, 1, &g_hueImage, 1, ch, 1 );//从输入中拷贝某通道到输出中特定的通道
41 
42     namedWindow( WINDOW_NAME , CV_WINDOW_AUTOSIZE );
43     createTrackbar("色调组距 ", WINDOW_NAME , &g_bins, 180, on_BinChange );
44     on_BinChange(0, 0);
45 
46     imshow( WINDOW_NAME , g_srcImage );
47     waitKey(0);
48 }

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opencv学习之路(20)、直方图应用

标签:har   const   read   point   pen   create   灰度   统计   class   

原文地址:http://www.cnblogs.com/little-monkey/p/7401466.html

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