#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace cv;
/// Global variables
Mat src, dst;
Mat map_x, map_y;
char* remap_window = "Remap demo";
int ind = 0;
/// Function Headers
void update_map( void );
/**
* @function main
*/
int main( int argc, char** argv )
{
/// Load the image
src = imread( argv[1], 1 );
/// Create dst, map_x and map_y with the same size as src:
dst.create( src.size(), src.type() );
map_x.create( src.size(), CV_32FC1 );
map_y.create( src.size(), CV_32FC1 );
/// Create window
namedWindow( remap_window, CV_WINDOW_AUTOSIZE );
/// Loop
while( true )
{
/// Each 1 sec. Press ESC to exit the program
int c = waitKey( 1000 );
if( (char)c == 27 )
{ break; }
/// Update map_x & map_y. Then apply remap
update_map();
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) );
/// Display results
imshow( remap_window, dst );
}
return 0;
}
/**
* @function update_map
* @brief Fill the map_x and map_y matrices with 4 types of mappings
*/
void update_map( void )
{
ind = ind%4;
for( int j = 0; j < src.rows; j++ )
{ for( int i = 0; i < src.cols; i++ )
{
switch( ind )
{
case 0:
if( i > src.cols*0.25 && i < src.cols*0.75 && j > src.rows*0.25 && j < src.rows*0.75 )
{
map_x.at<float>(j,i) = 2*( i - src.cols*0.25 ) + 0.5 ;
map_y.at<float>(j,i) = 2*( j - src.rows*0.25 ) + 0.5 ;
}
else
{ map_x.at<float>(j,i) = 0 ;
map_y.at<float>(j,i) = 0 ;
}
break;
case 1:
map_x.at<float>(j,i) = i ;
map_y.at<float>(j,i) = src.rows - j ;
break;
case 2:
map_x.at<float>(j,i) = src.cols - i ;
map_y.at<float>(j,i) = j ;
break;
case 3:
map_x.at<float>(j,i) = src.cols - i ;
map_y.at<float>(j,i) = src.rows - j ;
break;
} // end of switch
}
}
ind++;
}
首先准备程序用到的变量:
Mat src, dst;
Mat map_x, map_y;
char* remap_window = "Remap demo";
int ind = 0;
加载一幅图像:
src = imread( argv[1], 1 );
创建目标图像和两个映射矩阵.( x 和 y )
dst.create( src.size(), src.type() );
map_x.create( src.size(), CV_32FC1 );
map_y.create( src.size(), CV_32FC1 );
创建一个窗口用于展示结果.
namedWindow( remap_window, CV_WINDOW_AUTOSIZE );
建立一个间隔1000毫秒的循环,每次循环执行更新映射矩阵参数并对源图像进行重映射处理(使用 mat_x 和 mat_y),然后把更新后的目标图像显示出来:
while( true )
{
/// Each 1 sec. Press ESC to exit the program
int c = waitKey( 1000 );
if( (char)c == 27 )
{ break; }
/// Update map_x & map_y. Then apply remap
update_map();
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) );
/// Display results
imshow( remap_window, dst );
}
上面用到的重映射函数 remap. 参数说明:
如何更新重映射矩阵 mat_x 和 mat_y? 请继续看:
更新重映射矩阵: 我们将分别使用4种不同的映射:
图像宽高缩小一半,并显示在中间:
所有成对的参数 处理后都符合:
和
图像上下颠倒:
图像左右颠倒:
同时执行b和c的操作:
下面的代码片段说明上述的映射过程. 在这里 map_x 代表第一个坐标 h(i,j) , map_y 是第二个坐标.
for( int j = 0; j < src.rows; j++ ) { for( int i = 0; i < src.cols; i++ ) { switch( ind ) { case 0: if( i > src.cols*0.25 && i < src.cols*0.75 && j > src.rows*0.25 && j < src.rows*0.75 ) { map_x.at<float>(j,i) = 2*( i - src.cols*0.25 ) + 0.5 ; map_y.at<float>(j,i) = 2*( j - src.rows*0.25 ) + 0.5 ; } else { map_x.at<float>(j,i) = 0 ; map_y.at<float>(j,i) = 0 ; } break; case 1: map_x.at<float>(j,i) = i ; map_y.at<float>(j,i) = src.rows - j ; break; case 2: map_x.at<float>(j,i) = src.cols - i ; map_y.at<float>(j,i) = j ; break; case 3: map_x.at<float>(j,i) = src.cols - i ; map_y.at<float>(j,i) = src.rows - j ; break; } // end of switch } } ind++; }
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