OpenCv 004---图像像素的读写操作

 本次对像素的操作一共使用了五种方法，并进行计时对比，最终Opencv中的Copy方式速度是最快的，次之是指针遍历方式。

有一点就是为什么迭代的方式会比数组遍历的方式还要慢那么多，正常应该是比数组快一些才是正确的。

 

#include "opencv2\opencv.hpp"
#include <iostream>

using namespace std;
using namespace cv;

bool copyByArrayWay(Mat srcImg, Mat &resultImg);//数组at遍历方式
bool copyByRowPtrWay(Mat srcImg, Mat &resultImg);//行指针遍历方式
bool copyByPtrWay(Mat srcImg, Mat &resultImg);//指针遍历方式
bool copyByIteratorWay(Mat srcImg, Mat &resultImg);//迭代方式
bool copyByOpenCv(Mat srcImg, Mat &resultImg);//OpenCv copy方式
int main(int argv, char** argc)
{
    Mat src = imread("G:\\CVworkstudy\\program_wwx\\研习社140课时\\ZhaiZhigang140\\lena.jpg");
    if (src.empty())
    {
        printf("Could not load image...\n");
        return -1;
    }
    int64 startTime, endTime;
    double usedTime;

    ////数组遍历方式
    Mat arrayWayResult = Mat::zeros(src.size(), src.type());
    startTime = getTickCount();
    copyByArrayWay(src, arrayWayResult);
    endTime = getTickCount();
    usedTime = (endTime - startTime) / getTickFrequency() * 1000;
    cout << "数组遍历方式耗时:" << usedTime << "毫秒" << endl;
    imshow("arrayWay", arrayWayResult);

    ////行指针遍历方式
    Mat rowPtrWayResult = Mat::zeros(src.size(), src.type());
    startTime = getTickCount();
    copyByRowPtrWay(src, rowPtrWayResult);
    endTime = getTickCount();
    usedTime = (endTime - startTime) / getTickFrequency() * 1000;
    cout << "行指针遍历方式耗时:" << usedTime << "毫秒" << endl;
    imshow("rowPtrWay", rowPtrWayResult);

    ////指针方式遍历
    Mat ptrWayResult = Mat::zeros(src.size(), src.type());
    startTime = getTickCount();
    copyByPtrWay(src, ptrWayResult);
    endTime = getTickCount();
    usedTime = (endTime - startTime) / getTickFrequency() * 1000;
    cout << "指针遍历方式耗时:" << usedTime << "毫秒" << endl;
    imshow("ptrWay", ptrWayResult);

    ////迭代方式遍历
    Mat iterWayResult = Mat::zeros(src.size(), src.type());
    startTime = getTickCount();
    copyByIteratorWay(src, iterWayResult);
    endTime = getTickCount();
    usedTime = (endTime - startTime) / getTickFrequency() * 1000;
    cout << "迭代方式耗时:" << usedTime << "毫秒" << endl;
    imshow("iterWay", iterWayResult);

    ////OpenCv copy方式
    Mat copyWayResult = Mat::zeros(src.size(), src.type());
    startTime = getTickCount();
    copyByOpenCv(src, copyWayResult);
    endTime = getTickCount();
    usedTime = (endTime - startTime) / getTickFrequency() * 1000;
    cout << "Opencv copy方式耗时:" << usedTime << "毫秒" << endl;
    imshow("OpencvCopyWay", copyWayResult);
    
    waitKey(0);
    return 0;
}

//数组遍历方式 at
bool copyByArrayWay(Mat srcImg,Mat &resultImg)
{
    if (srcImg.empty())
    {
        printf("Could not load image...\n");
        return false;
    }
    int rows = srcImg.rows;
    int cols = srcImg.cols;
    int ch = srcImg.channels();
    for (int row = 0; row < rows; row++) {
        for (int col = 0; col < cols;col++) {
            if (ch == 3) {
                resultImg.at<Vec3b>(row, col) = srcImg.at<Vec3b>(row,col);

            }
            else if (ch == 1) {
                resultImg.at<uchar>(row, col) = srcImg.at<uchar>(row, col);
            }
        }
    }
    return true;
}

//行指针遍历方式
bool copyByRowPtrWay(Mat srcImg, Mat &resultImg)
{
    if (srcImg.empty())
    {
        printf("Could not load image...\n");
        return false;
    }
    int rows = srcImg.rows;
    int rowPixelNums = (srcImg.cols) * (srcImg.channels());
    for (int row = 0; row < rows; row++) {
        uchar *srcRowPtr = srcImg.ptr<uchar>(row);
        uchar *resultRowPtr = resultImg.ptr<uchar>(row);
        for (int pixelNum = 0; pixelNum < rowPixelNums; pixelNum++) {
            resultRowPtr[pixelNum] = srcRowPtr[pixelNum];
        }
    }
    return true;
}

//指针遍历方式
bool copyByPtrWay(Mat srcImg, Mat &resultImg)
{
    if (srcImg.empty()) {
        printf("Could not load image...\n");
        return false;
    }
    int ch = srcImg.channels();
    int totalPixelNums = (srcImg.rows) * (srcImg.cols) * ch;
    uchar *srcRowPtr = srcImg.ptr<uchar>(0);
    uchar *resultRowPtr = resultImg.ptr<uchar>(0);
    for (int pixel = 0; pixel < totalPixelNums; pixel++) {
        resultRowPtr[pixel] = srcRowPtr[pixel];
    }
    return true;
}

//迭代方式
bool copyByIteratorWay(Mat srcImg, Mat &resultImg)
{
    if (srcImg.empty()) {
        printf("Could not load image...\n");
        return false;
    }
    int ch = srcImg.channels();
    if (ch == 3) {
        Mat_<Vec3b>::iterator srcPtrBegin = srcImg.begin<Vec3b>();
        Mat_<Vec3b>::iterator outPtrBegin = resultImg.begin<Vec3b>();
        Mat_<Vec3b>::iterator srcPtrEnd = srcImg.end<Vec3b>();
        while (srcPtrBegin != srcPtrEnd) {
            *outPtrBegin = *srcPtrBegin;
            srcPtrBegin++;
            outPtrBegin++;
        }
        return true;
    }
    else if (ch == 1) {
        Mat_<uchar>::iterator srcPtrBegin = srcImg.begin<uchar>();
        Mat_<uchar>::iterator outPtrBegin = resultImg.begin<uchar>();
        Mat_<uchar>::iterator srcPtrEnd = srcImg.end<uchar>();
        while (srcPtrBegin != srcPtrEnd) {
            *outPtrBegin = *srcPtrBegin;
            srcPtrBegin++;
            outPtrBegin++;
        }
        return true;
    }
    else
        return false;
}

//OpenCv copy方式
bool copyByOpenCv(Mat srcImg, Mat &resultImg)
{
    if (srcImg.empty()) {
        printf("Could not load image...\n");
        return false;
    }
    srcImg.copyTo(resultImg);
    return true;
}