opencv-图像扫描，查表和处理时间选择

目标：

如何扫描图像中的每一个像素点？

Opencv如何存储像素矩阵值？

如何测试算法的性能？

#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <iostream>#include <sstream>using namespace std;using namespace cv;void help(){    cout        << "\n--------------------------------------------------------------------------" << endl        << "This program shows how to scan image objects in OpenCV (cv::Mat). As use case"        << " we take an input image and divide the native color palette (255) with the "  << endl        << "input. Shows C operator[] method, iterators and at function for on-the-fly item address calculation."<< endl        << "Usage:"                                                                       << endl        << "./howToScanImages imageNameToUse divideWith [G]"                              << endl        << "if you add a G parameter the image is processed in gray scale"                << endl        << "--------------------------------------------------------------------------"   << endl        << endl;}Mat& ScanImageAndReduceC(Mat& I, const uchar* table);Mat& ScanImageAndReduceIterator(Mat& I, const uchar* table);Mat& ScanImageAndReduceRandomAccess(Mat& I, const uchar * table);int main( int argc, char* argv[]){    help();    if (argc < 3)    {        cout << "Not enough parameters" << endl;        return -1;    }    Mat I, J;    if( argc == 4 && !strcmp(argv[3],"G") )//argc==4并且argv[3]='G'        //I = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);I = imread("G:\\basketballdrill0.bmp",0);//灰度图    else        //I = imread(argv[1], CV_LOAD_IMAGE_COLOR);I = imread("G:\\basketballdrill1.bmp",1);//彩色图    if (!I.data)    {        //cout << "The image" << argv[1] << " could not be loaded." << endl;cout << "The image" << "G:\\basketballdrill0.bmp" << " could not be loaded." << endl;        return -1;    }    //int divideWith; // convert our input string to number - C++ style    //stringstream s;    //s << argv[2];//写入流执行数据结构变换    //s >> divideWith;    //if (!s)    //{    //    cout << "Invalid number entered for dividing. " << endl;    //    return -1;    //}uchar table[256];    //for (int i = 0; i < 256; ++i)    //  table[i] = divideWith* (i/divideWith);const int times = 100;//各个运算循环次数常量100//ScanImageAndReduceC运算时间---    double t;    t = (double)getTickCount();    for (int i = 0; i < times; ++i)    {        cv::Mat clone_i = I.clone();        J = ScanImageAndReduceC(clone_i, table);    }    t = 1000*((double)getTickCount() - t)/getTickFrequency();    t /= times;    cout << "Time of reducing with the C operator [] (averaged for "<< times << " runs): " << t << " milliseconds."<< endl;//ScanImageAndReduceIterator运算时间---    t = (double)getTickCount();    for (int i = 0; i < times; ++i)    {        cv::Mat clone_i = I.clone();        J = ScanImageAndReduceIterator(clone_i, table);    }    t = 1000*((double)getTickCount() - t)/getTickFrequency();    t /= times;    cout << "Time of reducing with the iterator (averaged for "    << times << " runs): " << t << " milliseconds."<< endl;//ScanImageAndReduceRandomAccess运算时间---    t = (double)getTickCount();    for (int i = 0; i < times; ++i)    {        cv::Mat clone_i = I.clone();        ScanImageAndReduceRandomAccess(clone_i, table);    }    t = 1000*((double)getTickCount() - t)/getTickFrequency();    t /= times;    cout << "Time of reducing with the on-the-fly address generation - at function (averaged for "    << times << " runs): " << t << " milliseconds."<< endl;//The Core FunctionLTU    Mat lookUpTable(1, 256, CV_8U);    uchar* p = lookUpTable.data;    for( int i = 0; i < 256; ++i)        p[i] = table[i];//LUT运算时间    t = (double)getTickCount();    for (int i = 0; i < times; ++i)        LUT(I, lookUpTable, J);    t = 1000*((double)getTickCount() - t)/getTickFrequency();    t /= times;    cout << "Time of reducing with the LUT function (averaged for "    << times << " runs): " << t << " milliseconds."<< endl;    return 0;}Mat& ScanImageAndReduceC(Mat& I, const uchar* const table){    // accept only char type matrices    CV_Assert(I.depth() != sizeof(uchar));    int channels = I.channels();    int nRows = I.rows;    int nCols = I.cols * channels;    if (I.isContinuous())    {        nCols *= nRows;        nRows = 1;    }    int i,j;    uchar* p;    for( i = 0; i < nRows; ++i)    {        p = I.ptr<uchar>(i);        for ( j = 0; j < nCols; ++j)        {            p[j] = table[p[j]];        }    }    return I;}Mat& ScanImageAndReduceIterator(Mat& I, const uchar* const table){    // accept only char type matrices    CV_Assert(I.depth() != sizeof(uchar));    const int channels = I.channels();    switch(channels)    {    case 1:        {            MatIterator_<uchar> it, end;            for( it = I.begin<uchar>(), end = I.end<uchar>(); it != end; ++it)                *it = table[*it];            break;        }    case 3:        {            MatIterator_<Vec3b> it, end;            for( it = I.begin<Vec3b>(), end = I.end<Vec3b>(); it != end; ++it)            {                (*it)[0] = table[(*it)[0]];                (*it)[1] = table[(*it)[1]];                (*it)[2] = table[(*it)[2]];            }        }    }    return I;}Mat& ScanImageAndReduceRandomAccess(Mat& I, const uchar* const table){    // accept only char type matrices    CV_Assert(I.depth() != sizeof(uchar));    const int channels = I.channels();    switch(channels)    {    case 1:        {            for( int i = 0; i < I.rows; ++i)                for( int j = 0; j < I.cols; ++j )                    I.at<uchar>(i,j) = table[I.at<uchar>(i,j)];            break;        }    case 3:        {         Mat_<Vec3b> _I = I;         for( int i = 0; i < I.rows; ++i)            for( int j = 0; j < I.cols; ++j )               {                   _I(i,j)[0] = table[_I(i,j)[0]];                   _I(i,j)[1] = table[_I(i,j)[1]];                   _I(i,j)[2] = table[_I(i,j)[2]];            }         I = _I;         break;        }    }    return I;}