opencv之图像差分（4）

落日映苍穹つ 2022-05-28 11:09 183阅读 0赞

1.图像差分后取灰度值

main.cpp

#include <stdio.h>
    #include <stdlib.h>
    #include <math.h>
    #include <opencv2/opencv.hpp>
    
    using namespace cv;
    void onTrackerSlid(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos);
    
    int main()
    {
        Mat srcimage1 = imread("1.png");
        Mat srcimage2 = imread("2.png");
        Mat dstimage;
        Mat dstimage1;
        dstimage.create(srcimage1.rows, srcimage1.cols, srcimage1.type());
        dstimage1.create(srcimage1.rows, srcimage1.cols, srcimage1.type());
        onTrackerSlid(srcimage1, srcimage2, dstimage, 100);   //将图1与图2的差分结果保存在dstimage中
        namedWindow("srcimage1", CV_WINDOW_AUTOSIZE);
        namedWindow("srcimage2", CV_WINDOW_AUTOSIZE);
        namedWindow("dstimage", CV_WINDOW_AUTOSIZE);
        imshow("srcimage1", srcimage1);
        imshow("srcimage2", srcimage2);
        imshow("dstimage", dstimage);
        cvtColor(dstimage, dstimage, COLOR_RGB2GRAY);
        threshold(dstimage, dstimage1, 150, 255, THRESH_BINARY);   //记得加-lopencv_imgproc320
        namedWindow("dstimage1", CV_WINDOW_AUTOSIZE);
        imshow("dstimage1", dstimage1);
    
        waitKey(0);
        return 0;
    }
    
    void onTrackerSlid(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos)
    {
        uchar *data1 = NULL;
        uchar *data2 = NULL;
        uchar *data3 = NULL;
        //uchar *data = NULL;
        int i, j;
    
        outputimage = inputimage1.clone();
        int rowNumber = outputimage.rows;
        int colNumber = outputimage.cols*outputimage.channels();
        int step = outputimage.step/sizeof(uchar);
        data1 = (uchar*)inputimage1.data;
        data2 = (uchar*)inputimage2.data;
        data3 = (uchar*)outputimage.data;
    
        for(i = 0; i < rowNumber; i++)
        {
            //data = (uchar*)outputimage.ptr<uchar>(i);   //获取第i行的首地址
            for(j = 0; j < colNumber; j++)
            {
                if(fabs(data2[i*step + j] - data1[i*step + j]) > pos)
                    data3[i*step + j] = 255;
                else
                    data3[i*step + j] = 0;
            }
        }
    }

结果

![70][]

2. 图像差分后按权重处理

main.cpp

#include <stdio.h>
    #include <stdlib.h>
    #include <math.h>
    #include <opencv2/opencv.hpp>
    #include <opencv2/imgproc.hpp>
    
    using namespace cv;
    void onTrackerSlid(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos);
    
    int main()
    {
        double alphaValue = 1;
        double betaValue = 1;
    
        Mat image1 = imread("1.png");
        Mat image2 = imread("2.png");
        Mat image3 = imread("3.png");
        Mat image4 = imread("4.png");
    
        //cvtColor(image1, image1, COLOR_RGB2GRAY);
        //cvtColor(image2, image2, COLOR_RGB2GRAY);
    
        Mat dstimage1;
        Mat dstimage2;
        Mat dstimage3;
        Mat dst1;
        Mat dst2;
        dstimage1.create(image1.rows, image1.cols, image1.type());
        dstimage2.create(image1.rows, image1.cols, image1.type());
        dstimage3.create(image1.rows, image1.cols, image1.type());
        dst1.create(image1.rows, image1.cols, image1.type());
        dst2.create(image1.rows, image1.cols, image1.type());
    
        onTrackerSlid(image1, image2, dstimage1, 94);   //将图1与图2的差分结果保存在dstimage1中
        onTrackerSlid(image1, image3, dstimage2, 94);   //图1与图3
        onTrackerSlid(image1, image4, dstimage3, 94);    //图1与图4
    
        //betaValue = (1.0 - alphaValue);
        addWeighted(dstimage1, alphaValue, dstimage2, betaValue, 0.0, dst1);  //线性混合操作
        addWeighted(dst1, alphaValue, dstimage3, betaValue, 0.0, dst2);
    
        //bitwise_and(dstimage1, dstimage2, dst1);   //逻辑交运算，这里不适用
        //bitwise_and(dst1, dstimage3, dst2);
    
    
        namedWindow("dstimage1", CV_WINDOW_AUTOSIZE);
        namedWindow("dstimage2", CV_WINDOW_AUTOSIZE);
        namedWindow("dstimage3", CV_WINDOW_AUTOSIZE);
        namedWindow("dst1", CV_WINDOW_AUTOSIZE);
        namedWindow("dst2", CV_WINDOW_AUTOSIZE);
    
        //cvtColor(dst2, dst2, COLOR_RGB2GRAY);
    
        imwrite("last.jpg", dst2);      //将dst2输出到文件last.jpg中
    
        imshow("dstimage1", dstimage1);
        imshow("dstimage2", dstimage2);
        imshow("dstimage3", dstimage3);
        imshow("dst1", dst1);
        imshow("dst2", dst2);
    
        waitKey(0);
        return 0;
    }
    
    void onTrackerSlid(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos)
    {
        uchar *data1 = NULL;
        uchar *data2 = NULL;
        uchar *data3 = NULL;
        int i, j;
    
        outputimage = inputimage1.clone();
        int rowNumber = outputimage.rows;
        int colNumber = outputimage.cols*outputimage.channels();
        int step = outputimage.step/sizeof(uchar);
        data1 = (uchar*)inputimage1.data;
        data2 = (uchar*)inputimage2.data;
        data3 = (uchar*)outputimage.data;
    
        for(i = 0; i < rowNumber; i++)
        {
            for(j = 0; j < colNumber; j++)
            {
                if(fabs(data2[i*step + j] - data1[i*step + j]) > pos)
                    data3[i*step + j] = 255;
                else
                    data3[i*step + j] = 0;
            }
        }
    }

结果

![70 1][]

![70 2][]

[70]: /images/20220528/6bfb8ed3e33f4f65b49d9b55880c745d.png
[70 1]: /images/20220528/075aa175d65c43939a94297164fedc03.png
[70 2]: /images/20220528/3ec5e29822b44d6abdf9b21adf5cdb7b.png