OpenCV 三种图像遍历方法

实验目的：

通过颜色压缩（color reduction）示例理解学习OpenCV中遍历图像的三种方法；

实验代码：

#include
#include
#include

using namespace cv;
using namespace std;

// 1：使用指针遍历图像
void colorReduceByPointer(Mat& image, int div = 64)
{
    int nRows = image.rows;
    int nCols = image.cols * image.channels();

    if (image.isContinuous())
    {
        nCols *= nRows;
        nRows = 1; // 如果连续，外层循环执行只需一次，以此提高执行效率
    }

    for (int i = 0; i < nRows; ++i)
    {
        uchar* data = image.ptr(i);
        for (int j = 0; j < nCols; ++j)
        {
            data[j] = data[j] / div*div + div / 2;
        }
    }
}

// 2：使用at遍历图像
void colorReduceByAtMethod(Mat& image, int div = 64)
{
    int nRows = image.rows;
    int nCols = image.cols;

    if (image.channels() == 1)
    {
        for (int i = 0; i < nRows; ++i)
        {
            for (int j = 0; j < nCols; ++j)
            {
                image.at(i, j) = image.at(i, j) / div * div + div / 2;
            }
        }
    }
    else if (image.channels() == 3)
    {
        for (int i = 0; i < nRows; ++i)
        {
            for (int j = 0; j < nCols; ++j)
            {
                image.at(i, j)[0] = image.at(i, j)[0] / div*div + div / 2;
                image.at(i, j)[1] = image.at(i, j)[1] / div*div + div / 2;
                image.at(i, j)[2] = image.at(i, j)[2] / div*div + div / 2;
            }
        }
    }
}

// 3：使用迭代器进行图像的遍历
void colorReduceByIterator(Mat& image, int div = 64)
{
    const int channels = image.channels();
    switch (channels)
    {
        case 1:
        {
            MatIterator_begin, end;
            for (begin = image.begin(), end = image.end(); begin != end; ++begin)
            {
                *begin = *begin / div*div + div / 2;
            }
            break;
        }
        case 3:
        {
            MatIterator_ begin, end;
            for (begin = image.begin(), end = image.end(); begin != end; ++begin)
            {
                (*begin)[0] = (*begin)[0] / div * div + div / 2;
                (*begin)[1] = (*begin)[1] / div * div + div / 2;
                (*begin)[2] = (*begin)[2] / div * div + div / 2;
            }
            break;
        }
    }
}


int main()
{
    Mat image;
    image = imread("E:\\dataset\\image.jpg");
    if (!image.data)
        return -1;
    //cvtColor(image, image, CV_BGR2GRAY);
    //colorReduceByAtMethod(image);
    //colorReduceByPointer(image);
    colorReduceByIterator(image);
    namedWindow("after");
    imshow("after", image);
    cvWaitKey(-1);
    destroyAllWindows();
    return 0;
}