Mat A;

Mat B=A(Range::(5,9),Range(1,3));  //表示5-9行(不包括9),1-3列(不包括3)

//在图像的右下角定义一个ROI

cv::Mat imageROI(image,cv::Rect(image.cols-logo.cols,

                                image.rows-logo.rows,

                                logo.cols,

                                logo.rows));

或者

cv::Mat imageROI=image(cv::Rect(image.cols-logo.cols,

                                image.rows-logo.rows,

                                logo.cols,

                                logo.rows));

//遍历像素值

#include <iostream>

#include "opencv2/opencv.hpp"

using namespace std;

int main(int argc, char* argv[]) {

	cv::Mat grayim(600, 800, CV_8UC1);

	cv::Mat colorim(600, 800, CV_8UC3);

	//遍历所有像素,并设置像素值

	for(int i = 0;i < grayim.rows; ++i)

		for(int j = 0; j < grayim.cols; ++j)

			grayim.at<uchar>(i,j) = (i+j)%255;

	//遍历所有像素,并设置像素值

	for(int i=0; i<colorim.rows; ++i)

		for(int j=0; j<colorim.cols; ++j)

		{

			cv::Vec3b pixel;

			pixel[0] = i%255;  //Blue

			pixel[1] = j%255;  //Green

			pixel[2] = 0;      //Red

			colorim.at<cv::Vec3b>(i,j) = pixel;

		}

	cv::imshow("grayim",grayim);

	cv::imshow("colorim",colorim);

	cv::waitKey(0);

	return 0;

}

#include <iostream>

#include "opencv2/opencv.hpp"

using namespace std;

int main(int argc, char* argv[]) {

	cv::Mat grayim(600,800,CV_8UC1);

	cv::Mat colorim(600,800,CV_8UC3);

	//遍历所有像素,并设置像素值

	for( int i = 0; i < grayim.rows; ++i) {

		//获取第i行首像素指针

		uchar* p = grayim.ptr<uchar>(i);

		//对第i的每个像素操作

		for(int j = 0;j < grayim.cols; ++j)

			p[j] = (i+j)%255;

	}

	//遍历所有像素,并设置像素值

	for( int i = 0; i<colorim.rows; ++i) {

		//获取第i行首像素指针

		cv::Vec3b* p=colorim.ptr<cv::Vec3b>(i);

		for( int j = 0; j < colorim.cols; ++j) {

			p[j][0] = i%255;  //Blue

			p[j][1] = j%255;  //Green

			p[j][2] = 0;     //Red

		}

	}

	imshow("grayim", grayim);

	imshow("colorim", colorim);

	cv::waitKey(0);

	return 0;

}

#include <iostream>

#include "opencv2/opencv.hpp"

using namespace std;

int main(int argc, char* argv[]) {

	cv::Mat grayim(600, 800, CV_8UC1);

	cv::Mat colorim(600, 800, CV_8UC3);

	//遍历所有像素,并设置像素值

	cv::MatIterator_<uchar> grayit, grayend;

	for( grayit = grayim.begin<uchar>(), grayend = grayim.end<uchar>(); grayit != grayend; ++grayit)

		*grayit = rand()%255;

	//遍历所有像素,并设置像素值

	cv::MatIterator_<cv::Vec3b> colorit,colorend;

	for( colorit = colorim.begin<cv::Vec3b>(), colorend = colorim.end<cv::Vec3b>(); colorit != colorend; ++colorit) {

		(*colorit)[0] = rand()%255;  //Blue

		(*colorit)[1] = rand()%255;  //Green

		(*colorit)[2] = rand()%255;  //Red

	}

	//显示结果

	cv::imshow("grayim", grayim);

	cv::imshow("colorim", colorim);

	cv::waitKey(0);

	return 0;

}

//用Mat_模板操作图像

cv::Mat_<uchar> im2(image);

im2(50,100)=0;  // 访问第50行,第100列处那个值

cv::Mat inverseColor6(cv::Mat srcImage)

{

	int row = srcImage.rows;

	int col = srcImage.cols;

	cv::Mat tempImage = srcImage.clone();

	// 建立LUT 反色table

	uchar LutTable[256];

	for (int i = 0; i < 256; ++i)

		LutTable[i] = 256 - i;

	cv::Mat lookUpTable(1, 256, CV_8U);

	uchar* pData = lookUpTable.data;

	// 建立映射表

	for (int i = 0; i <256; ++i)

		pData[i] = LutTable[i];

	// 应用搜索表进行查找

	cv::LUT(srcImage, lookUpTable, tempImage);

	return tempImage;

}

//test.cpp

void colorReduce(cv::Mat image,int div=64){

	int nl=image.rows;  //行数

	//每行的元素数量

	int nc=image.cols*image.channels();

	for(int j=0;j<nl;j++){

		//取得行j的地址

		uchar* data=image.ptr<uchar>(j);

		for(int i=0;i<nc;i++){

			//处理每个像素

			data[i]=data[i]/div*div+div/2;

		}

	}

}

void colorReduce(cv::Mat image,int div=64){

	//在初始位置获得迭代器

	cv::Mat_<cv::Vec3b>::iterator it=image.begin<cv::Vec3b>();

	//获得结束位置

	cv::Mat_<cv::Vec3b>::iterator itend=image.end<cv::Vec3b>();

	//循环遍历所有像素

	for(;it!=itend;++it){

		//处理每个像素

		(*it)[0]=(*it)[0]/div*div+div/2;

		(*it)[1]=(*it)[1]/div*div+div/2;

		(*it)[2]=(*it)[2]/div*div+div/2;

	}

}

void sharpen(const cv::Mat& image,cv::Mat& result){

	//判断是否需要分配图像数据,如果需要,就分配

	result.create(image.size(),image.type());

	int nchannels=image.channels();		//获得通道数

	//处理所有行(除了第一行和最后一行)

	for(int j=1;j<image.rows-1;j++){

		const uchar* previous=image.ptr<const uchar>(j-1);  //上一行

		const uchar* current=image.ptr<const uchar>(j);	   //当前行

		const uchar* next=image.ptr<const uchar>(j+1);	   //下一行

		uchar* output=result.ptr<uchar>(j);					//输出行

		for(int i=nchannels;i<(image.cols-1)*nchannels;i++){

			*output++=cv::saturate_cast<uchar>(

				5*current[i]-current[i-nchannels]-current[i+nchannels-previous[i]-next[i]]);

		}

	}

	//把未处理的像素设为0

	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));

}

int main()

{

	cv::Mat imag1=cv::imread("a.jpg");

	cv::Mat result;

	sharpen(imag1,result);

	cv::namedWindow("Image");

	cv::imshow("Image",result);

	cv::waitKey(0);

	system("pause");

	return 0;

}