Remapping

Goal

In this tutorial you will learn how to:

a. Use the OpenCV function @ref cv::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 \f$(x,y)\f$ as:

\f[g(x,y) = f ( h(x,y) )\f]

where \f$g()\f$ is the remapped image, \f$f()\f$ the source image and \f$h(x,y)\f$ is the mapping function that operates on \f$(x,y)\f$.
Let's think in a quick example. Imagine that we have an image \f$I\f$ and, say, we want to do a remap such that:

\f[h(x,y) = (I.cols - x, y )\f]

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

observe how the red circle changes positions with respect to x (considering \f$x\f$ the horizontal direction):
In OpenCV, the function @ref cv::remap offers a simple remapping implementation.

Code

-# 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

-# The tutorial code's is shown lines below. You can also download it from here @includelineno samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp

Explanation

-# Create some variables we will use: @code{.cpp} Mat src, dst; Mat map_x, map_y; char* remap_window = "Remap demo"; int ind = 0; @endcode -# Load an image: @code{.cpp} src = imread( argv[1], 1 ); @endcode -# Create the destination image and the two mapping matrices (for x and y ) @code{.cpp} dst.create( src.size(), src.type() ); map_x.create( src.size(), CV_32FC1 ); map_y.create( src.size(), CV_32FC1 ); @endcode -# Create a window to display results @code{.cpp} namedWindow( remap_window, WINDOW_AUTOSIZE ); @endcode -# Establish a loop. Each 1000 ms we update our mapping matrices (mat_x and mat_y) and apply them to our source image: @code{.cpp} 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, INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) );

  /// Display results
  imshow( remap_window, dst );
}
@endcode
The function that applies the remapping is @ref cv::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 \f$h(i,j)\f$
-   **map_y**: Same as above, but in y direction. Note that *map_y* and *map_x* are both of
    the same size as *src*
-   **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:

-# Updating the mapping matrices: We are going to perform 4 different mappings: -# Reduce the picture to half its size and will display it in the middle: \f[h(i,j) = ( 2i - src.cols/2 + 0.5, 2j - src.rows/2 + 0.5)\f] for all pairs \f$(i,j)\f$ such that: \f$\dfrac{src.cols}{4}<i<\dfrac{3 \cdot src.cols}{4}\f$ and \f$\dfrac{src.rows}{4}<j<\dfrac{3 \cdot src.rows}{4}\f$ -# Turn the image upside down: \f$h( i, j ) = (i, src.rows - j)\f$ -# Reflect the image from left to right: \f$h(i,j) = ( src.cols - i, j )\f$ -# Combination of b and c: \f$h(i,j) = ( src.cols - i, src.rows - j )\f$

This is expressed in the following snippet. Here, map_x represents the first coordinate of h(i,j) and map_y the second coordinate. @code{.cpp} for( int j = 0; j < src.rows; j++ ) { for( int i = 0; i < src.cols; i++ ) { switch( ind ) { case 0: if( i > src.cols0.25 && i < src.cols0.75 && j > src.rows0.25 && j < src.rows0.75 ) { map_x.at(j,i) = 2*( i - src.cols0.25 ) + 0.5 ; map_y.at(j,i) = 2( j - src.rows*0.25 ) + 0.5 ; } else { map_x.at(j,i) = 0 ; map_y.at(j,i) = 0 ; } break; case 1: map_x.at(j,i) = i ; map_y.at(j,i) = src.rows - j ; break; case 2: map_x.at(j,i) = src.cols - i ; map_y.at(j,i) = j ; break; case 3: map_x.at(j,i) = src.cols - i ; map_y.at(j,i) = src.rows - j ; break; } // end of switch } } ind++; } @endcode

Result

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

![](images/Remap_Tutorial_Original_Image.jpg)

-# This is the result of reducing it to half the size and centering it:

![](images/Remap_Tutorial_Result_0.jpg)

-# Turning it upside down:

![](images/Remap_Tutorial_Result_1.jpg)

-# Reflecting it in the x direction:

![](images/Remap_Tutorial_Result_2.jpg)

-# Reflecting it in both directions:

![](images/Remap_Tutorial_Result_3.jpg)

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