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

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 (x,y) as:

    g(x,y) = f ( h(x,y) )

    where g() is the remapped image, f() the source image and h(x,y) is the mapping function that operates on (x,y).

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

    h(x,y) = (I.cols - x, y )

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

    Original test image

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

    Original test image
  • 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 h(i,j)
    • 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:

      h(i,j) = ( 2*i - src.cols/2  + 0.5, 2*j - src.rows/2  + 0.5)

      for all pairs (i,j) such that: \dfrac{src.cols}{4}<i<\dfrac{3 \cdot src.cols}{4} and \dfrac{src.rows}{4}<j<\dfrac{3 \cdot src.rows}{4}

    2. Turn the image upside down: h( i, j ) = (i, src.rows - j)

    3. Reflect the image from left to right: h(i,j) = ( src.cols - i, j )

    4. Combination of b and c: h(i,j) = ( src.cols - i, src.rows - j )

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:

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

    Result 0 for remapping
  3. Turning it upside down:

    Result 0 for remapping
  4. Reflecting it in the x direction:

    Result 0 for remapping
  5. Reflecting it in both directions:

Result 0 for remapping

posted on 2017-12-20 17:44 zmj 阅读(129) 评论(0)  编辑 收藏 引用


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