Remapping {#tutorial_remap} ========= @tableofcontents @prev_tutorial{tutorial_generalized_hough_ballard_guil} @next_tutorial{tutorial_warp_affine} | | | | -: | :- | | Original author | Ana Huamán | | Compatibility | OpenCV >= 3.0 | 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: ![](images/Remap_Tutorial_Theory_0.jpg) observe how the red circle changes positions with respect to x (considering \f$x\f$ the horizontal direction): ![](images/Remap_Tutorial_Theory_1.jpg) - 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 @add_toggle_cpp - The tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp) @include samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp @end_toggle @add_toggle_java - The tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java) @include samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java @end_toggle @add_toggle_python - The tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py) @include samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py @end_toggle Explanation ----------- - Load an image: @add_toggle_cpp @snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Load @end_toggle @add_toggle_java @snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Load @end_toggle @add_toggle_python @snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Load @end_toggle - Create the destination image and the two mapping matrices (for x and y ) @add_toggle_cpp @snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Create @end_toggle @add_toggle_java @snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Create @end_toggle @add_toggle_python @snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Create @end_toggle - Create a window to display results @add_toggle_cpp @snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Window @end_toggle @add_toggle_java @snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Window @end_toggle @add_toggle_python @snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Window @end_toggle - Establish a loop. Each 1000 ms we update our mapping matrices (*mat_x* and *mat_y*) and apply them to our source image: @add_toggle_cpp @snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Loop @end_toggle @add_toggle_java @snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Loop @end_toggle @add_toggle_python @snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Loop @end_toggle - 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) = ( 2 \times i - src.cols/2 + 0.5, 2 \times j - src.rows/2 + 0.5)\f] for all pairs \f$(i,j)\f$ such that: \f$\dfrac{src.cols}{4}