Remapping

Goal

In this tutorial you will learn how to:

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

Theory

What is remapping?

• It is the process of taking pixels from one place in the image and locating them in another position in a new image.

• To accomplish the mapping process, it might be necessary to do some interpolation for non-integer pixel locations, since there will not always be a one-to-one-pixel correspondence between source and destination images.

• We can express the remap for every pixel location as:

  

  where is the remapped image, the source image and is the mapping function that operates on .

• Let’s think in a quick example. Imagine that we have an image and, say, we want to do a remap such that:

  

  What would happen? It is easily seen that the image would flip in the direction. For instance, consider the input image:

  

  observe how the red circle changes positions with respect to x (considering the horizontal direction):

  

• In OpenCV, the function remap offers a simple remapping implementation.

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: