#include<iostream>
#include<fstream>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace std;
using namespace cv;
const double pi = 3.141592;
Mat image;
void transform(Mat &pic ,int row ,int col)
{
//这一段程序实现:图像img -> ptr[][] -> 图像img2 的传递过程,即图像->二维数组->图像
int i = 0;
int j = 0;
namedWindow("原图");
imshow("原图", img);
Mat img2 = Mat(row, col, CV_8UC1);//图像img2:row*col大小
uchar **ptr = (uchar **)malloc(row*sizeof(uchar *));//二维数组ptr[][]
for (i = 0; i < row; i++)
ptr[i] = (uchar *)malloc(col*sizeof(uchar));
uchar *ptmp = NULL;//这是关键的指针!!
for (i = 0; i < row; i++)
{
ptmp = img2.ptr<uchar>(i);//指针指向img2的第i行
for (j = 0; j < col; j++)
{
ptr[i][j] = img.at<uchar>(i, j);//img的矩阵数据传给二维数组ptr[][]
ptmp[j] = ptr[i][j];//二维数组数据传给img2的第i行第j列
}
}
namedWindow("新图");
imshow("新图",img2);
// 等待100000 ms后窗口自动关闭
waitKey(100000);
}
int main()
{
//读取图像,图像为灰度图,单通道
Mat image = imread("pic.png", CV_LOAD_IMAGE_GRAYSCALE);
transform(image, image.rows, image.cols);
//显示原图
if (!image.empty())
imshow("image", image);
//计算A系数
myDct(A);
//转换成浮点数矩阵,进行dct变换
image.convertTo(fimage, CV_32FC1);//将图片转化成浮点数矩阵,然后进行dct的变换----------
imshow("压缩图", fimage);//dct变换后的图片
imshow("还原图", image);
waitKey(0);
return 0;
}
uchar** transform(Mat &img, int row, int col)
{
int i = 0, j = 0;
uchar **ptr = (uchar **)malloc(row*sizeof(uchar *));//二维数组ptr[][]
for (i = 0; i < row; i++)
ptr[i] = (uchar *)malloc(col*sizeof(uchar));
//新图的大小以及指向它的指针
Mat img2 = Mat(row, col, CV_8UC1);//图像img2:row*col大小
uchar *ptmp = NULL;//这是关键的指针!!
for (i = 0; i < row; i++)
{
ptmp = img2.ptr<uchar>(i);//指针指向img2的第i行
for (j = 0; j < col; j++)
{
ptr[i][j] = img.at<uchar>(i, j);//img的矩阵数据传给二维数组ptr[][]
ptmp[j] = ptr[i][j];//二维数组数据传给img2的第i行第j列
}
}
// namedWindow("新图");
// imshow("新图", img2);
// 等待100000 ms后窗口自动关闭
waitKey(100000);
return ptr;
}
外部函数调用:
#include<iostream>
#include<fstream>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace std;
using namespace cv;
const double pi = 3.141592;
void transform(Mat &pic, int row, int col)
{
//这一段程序实现:图像img -> ptr[][] -> 图像img2 的传递过程,即图像->二维数组->图像
int i = 0;
int j = 0;
namedWindow("原图");
imshow("原图", img);
Mat img2 = Mat(row, col, CV_8UC1);//图像img2:row*col大小
uchar **ptr = (uchar **)malloc(row*sizeof(uchar *));//二维数组ptr[][]
for (i = 0; i < row; i++)
ptr[i] = (uchar *)malloc(col*sizeof(uchar));
uchar *ptmp = NULL;//这是关键的指针!!
for (i = 0; i < row; i++)
{
ptmp = img2.ptr<uchar>(i);//指针指向img2的第i行
for (j = 0; j < col; j++)
{
ptr[i][j] = img.at<uchar>(i, j);//img的矩阵数据传给二维数组ptr[][]
ptmp[j] = ptr[i][j];//二维数组数据传给img2的第i行第j列
}
}
namedWindow("新图");
imshow("新图", img2);
// 等待100000 ms后窗口自动关闭
waitKey(100000);
}
int main()
{
//读取图像,图像为灰度图,单通道
Mat image = imread("pic.png", CV_LOAD_IMAGE_GRAYSCALE);
transform(image, image.rows, image.cols);
//显示原图
if (!image.empty())
imshow("image", image);
//转换成浮点数矩阵,进行dct变换
image.convertTo(fimage, CV_32FC1);//将图片转化成浮点数矩阵,然后进行dct的变换----------
imshow("压缩图", fimage);//dct变换后的图片
imshow("还原图", image);
waitKey(0);
return 0;
}
转自:https://blog.csdn.net/lqmiku/article/details/79110955
//2018.1.19_21:09 by Cooper Liu
//Questions? Contact me: [email protected]
//本程序为C++工程,编译环境需要配置openCV
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
//#include<opencv2/opencv.hpp>//如果要包含所有库
using namespace cv;
void main()
{
//这一段程序实现:图像img -> ptr[][] -> 图像img2 的传递过程,即图像->二维数组->图像
int i = 0, j = 0;
Mat img = imread("F:\\photoCollection\\flowergirl.png", 0);//读取图像img。0表示转换为灰度图像读入
int row = img.rows;
int col = img.cols;
namedWindow("原图");
imshow("原图", img);
Mat img2 = Mat(row, col, CV_8UC1);//图像img2:row*col大小
uchar **ptr = (uchar **)malloc(row*sizeof(uchar *));//二维数组ptr[][]
for (i = 0; i < row; i++)
ptr[i] = (uchar *)malloc(col*sizeof(uchar));
uchar *ptmp = NULL;//这是关键的指针!!
for (i = 0; i < row; i++)
{
ptmp = img2.ptr<uchar>(i);//指针指向img2的第i行
for (j = 0; j < col; j++)
{
ptr[i][j] = img.at<uchar>(i, j);//img的矩阵数据传给二维数组ptr[][]
ptmp[j] = ptr[i][j];//二维数组数据传给img2的第i行第j列
}
}
namedWindow("新图");
imshow("新图", img2);
// 等待100000 ms后窗口自动关闭
waitKey(100000);
}
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