opencv学习笔记 一 图像读取与操作

包括基本的图像读取，深拷贝和浅拷贝，salt，使用指针遍历图像，颜色缩减，图像锐化

#include <iostream>#include <opencv2\opencv.hpp>#include <opencv2\highgui\highgui.hpp>#define _CRT_SECURE_NO_DEPRECATEvoid salt(cv::Mat &image, int n);   //图像中随机元素设置为白色（255）void colreduc( cv::Mat &image, int div = 64);   //遍历图像颜色缩减void Sharp(const cv::Mat &image, cv::Mat &result);  //图像锐化int main(){    cv::Mat image2;    cv::Mat image = cv::imread("1.jpg");    std::cout << "size:" << image.size().height <<","<< image.size().width << std::endl;    image.copyTo(image2);            //图像拷贝，深拷贝    double duration;    duration = static_cast<double>(cv::getTickCount());  //时钟初始个数    Sharp(image, image2);    //经历总的时钟个数    duration = static_cast<double>(cv::getTickCount()) - duration;    //时间等于时钟个数除以频率    duration /= cv::getTickFrequency();                std::cout << "Time:" << duration << std::endl;    cv::namedWindow("Orignial image");    cv::imshow("Orignial image",image);    cv::namedWindow("Salt image");    cv::imshow("Salt image", image2);    cv::waitKey(0);    return 0;}void salt(cv::Mat &image, int n){    for (int k = 0; k < n; k++)    {        int i = rand() % image.cols;        int j = rand() % image.rows;        if (image.channels() == 1)        {            image.at<uchar>(j, i) = 255;        }        else if (image.channels() == 3)        {            image.at<cv::Vec3b>(j, i)[0] = 255;      //通道表示方法            image.at < cv::Vec3b>(j, i)[1] = 255;            image.at<cv::Vec3b>(j, i)[2] = 255;        }    }}//使用迭代器进行颜色缩减void colreduc(cv::Mat &image,int div){    //result.create(image.rows, image.cols, image.type());    //初始位置的迭代器    cv::Mat_<cv::Vec3b>::iterator it = image.begin<cv::Vec3b>();    cv::Mat_<cv::Vec3b>::iterator itend = image.end<cv::Vec3b>();    for (; it != itend; ++it)    {        (*it)[0] = (*it)[0] / div * div + div / 2;   //对元素进行操作        (*it)[1] = (*it)[1] / div * div + div / 2;        (*it)[2] = (*it)[2] / div * div + div / 2;    }    //指针遍历图像    /*int n = result.rows;    int nc = result.cols * result.channels();    uchar mask = 0xFF << 4;    for (int j = 0; j < n; j++)    {        const uchar* data_in = image.ptr<uchar>(j);        uchar* data_out = result.ptr<uchar>(j);        for (int i = 0; i < nc; i++)        {            data_out[i] = (data_in[i] & mask) + div / 2;        }    }*/}//图像锐化void Sharp(const cv::Mat &image, cv::Mat &result){    result.create(image.size(), image.type());    for (int j = 1; j < image.rows - 1; j++)    {        const uchar* current = image.ptr<const uchar>(j);        const uchar* up = image.ptr<const uchar>(j - 1);        const uchar* down = image.ptr<const uchar>(j + 1);        uchar* output = result.ptr<uchar>(j);        for (int i = 1; i < image.cols - 1; i++)        {            *output++ = cv::saturate_cast<uchar>( 5 * current[i] - current[i + 1] - current[i - 1] - up[i] - down[i]);        }    }    result.row(0).setTo(cv::Scalar(0));    result.row(result.rows - 1).setTo(cv::Scalar(0));    result.col(0).setTo(cv::Scalar(0));    result.col(result.cols - 1).setTo(cv::Scalar(0));}

注：
1.大多数的c++操作符都被重载了，所以可以写出例如:

result = 0.1 * image1 + 0.8 * image2