OpenCV Remapping

https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/remap/remap.html

Goal

In this tutorial you will learn how to:

1. Use the OpenCV function remap to implement simple remapping routines.

Theory

Code

1. What does this program do?
   • Loads an image
   • Each second, apply 1 of 4 different remapping processes to the image and display them indefinitely in a window.
   • Wait for the user to exit the program
2. The tutorial code’s is shown lines below. You can also download it from here

 #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++; } 

Explanation

1. Create some variables we will use:

   Mat src, dst; Mat map_x, map_y; char* remap_window = "Remap demo"; int ind = 0; 

2. Load an image:

   src = imread( argv[1], 1 ); 

3. Create the destination image and the two mapping matrices (for x and y )

   dst.create( src.size(), src.type() ); map_x.create( src.size(), CV_32FC1 ); map_y.create( src.size(), CV_32FC1 ); 

4. Create a window to display results

   namedWindow( remap_window, CV_WINDOW_AUTOSIZE ); 

5. Establish a loop. Each 1000 ms we update our mapping matrices (mat_x and mat_y) and apply them to our source image:

   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 ); } 

   The function that applies the remapping is remap. We give the following arguments:

   • src: Source image
   • dst: Destination image of same size as src
   • map_x: The mapping function in the x direction. It is equivalent to the first component of 
   • map_y: Same as above, but in y direction. Note that map_y and map_x are both of the same size as src
   • CV_INTER_LINEAR: The type of interpolation to use for non-integer pixels. This is by default.
   • BORDER_CONSTANT: Default

   How do we update our mapping matrices mat_x and mat_y? Go on reading:

6. Updating the mapping matrices: We are going to perform 4 different mappings:

   1. Reduce the picture to half its size and will display it in the middle:

      for all pairs  such that:  and 

   2. Turn the image upside down: 

   3. Reflect the image from left to right: 

   4. Combination of b and c: 

This is expressed in the following snippet. Here, map_x represents the first coordinate of h(i,j) and map_y the second coordinate.

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++; } 

Result

1. After compiling the code above, you can execute it giving as argument an image path. For instance, by using the following image:

2. This is the result of reducing it to half the size and centering it:

3. Turning it upside down:

4. Reflecting it in the x direction:

5. Reflecting it in both directions: