OpenCV与c语言图像融合

最新推荐文章于 2023-05-30 00:46:08 发布

原创最新推荐文章于 2023-05-30 00:46:08 发布 · 3.6k 阅读

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CC 4.0 BY-SA版权

本文介绍了一种使用OpenCV实现图像混合的技术，并通过C语言进行了手动实现。对比了两种方法的性能差异，展示了如何读取、混合及显示图像，对于理解图像处理中的加权求和非常有用。

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原文：http://blog.youkuaiyun.com/mjlsuccess/article/details/12400787
//#include "blending.h"
#include <opencv2/core.hpp>
//#include <iostream>
#include <opencv2/opencv.hpp>
#include <QString>
using namespace std;
using namespace cv;
void blending_test()
{
    Mat src1, src2, dst;
    double alpha = 0.5;
    double beta = 1-alpha;
    src1 = imread("11.jpg");
    src2 = imread("12.jpg");
    if(!src1.data) cout<<"error loading src1"<<endl;
    if(!src2.data) cout<<"Error loading src2"<<endl;
    addWeighted(src1, alpha, src2, beta, 0.0, dst);
    imshow("output1", dst);
//  waitKey(0);
}
//C语言自己实现
void blending()
{
    Mat src1, src2, dst;
    double alpha = 0.5;
    double beta = 1-alpha;
    double gama = 0;
    src1 = imread("11.jpg");
    src2 = imread("12.jpg");
    //判断两幅图片是否相同
    CV_Assert(src1.depth() == CV_8U);
    CV_Assert(src1.depth() == src2.depth());
    CV_Assert(src1.size() == src2.size());
    //为dst申请内存
    dst.create(src1.size(), src1.type());
    const int nChannels = src1.channels();
    if(!src1.data) cout<<"error loading src1"<<endl;
    if(!src2.data) cout<<"Error loading src2"<<endl;
    for (int i=0; i<src1.rows; i++)
    {
        const uchar* src1_ptr = src1.ptr<uchar>(i);
        const uchar* src2_ptr = src2.ptr<uchar>(i);
        uchar* dst_ptr  = dst.ptr<uchar>(i);
        for (int j=0; j<src1.cols*nChannels; j++)
        {
            dst_ptr[j] = src1_ptr[j]*alpha + src2_ptr[j]*beta + gama;
        }
    }
    imshow("output2",dst);
}
//下面是main函数部分
int main(int argc, char* argv[])
{
    double t;
    t = (double)getTickCount();
    blending_test();
    t = 1000*((double)getTickCount() - t)/getTickFrequency();
    printf("opencv time: %f ms\n",t);
    cout<<"opencv time:"<<t<<endl;
    t = (double)getTickCount();
    blending();
    t = 1000*((double)getTickCount() - t)/getTickFrequency();
    cout<<"c language time:"<<t<<"ms"<<endl;
    cvWaitKey(0);
    return 0;
}


imread()需要0.7ms左右
imshow特别需要时间，几百

addWeighted需要时间是2ms，连续三次需要3ms
但是c语言遍历版的需要3ms