| Landmark correspondence |
| Image Registration and Fusion Systems |
 | |  |
Landmark correspondence or point pattern matching is the process of finding correspondence between landmarks in two
images of a scene. If landmarks in only one of the images are given, corresponding landmarks in the second image can be
determined through a process known as template matching. If landmarks in both images are given, a point pattern matching
algorithm is required to determine the correspondence between the points. This software assumes that the images and,
therefore, corresponding landmarks in the images are related by an affine transformation.
An example of landmark correspondence by this algorithm is given below. In the images in the top row are landmarks (shown
by red dots) detected in two Landsat 5 images of a scene. The scene is relatively flat and because the sensor is very far from
the scene compared to variations in scene elevation, corresponding landmarks in the images can be considered relating by
an affine transformation, making it possible for this software to determine the correspondence between the landmarks. The
landmarks in the images are detected by a procedure described elsewhere (See the landmark detection page for details).
Although many detected landmarks exist in only one of the images due to considerable changes in scene between the times
the images were taken, there are landmarks that exist in both images. The algorithm is capable of finding the correspondence
between landmarks in such images and register the images. Registration of the images by an affine transformation (see the
auto affine registration page for details) using the obtained set of correspondences is shown in the left image in the bottom
row. Subtracting the registered images we obtain the right image in the bottom row, showing scene changes occurred
between the times the images were obtained.
images of a scene. If landmarks in only one of the images are given, corresponding landmarks in the second image can be
determined through a process known as template matching. If landmarks in both images are given, a point pattern matching
algorithm is required to determine the correspondence between the points. This software assumes that the images and,
therefore, corresponding landmarks in the images are related by an affine transformation.
An example of landmark correspondence by this algorithm is given below. In the images in the top row are landmarks (shown
by red dots) detected in two Landsat 5 images of a scene. The scene is relatively flat and because the sensor is very far from
the scene compared to variations in scene elevation, corresponding landmarks in the images can be considered relating by
an affine transformation, making it possible for this software to determine the correspondence between the landmarks. The
landmarks in the images are detected by a procedure described elsewhere (See the landmark detection page for details).
Although many detected landmarks exist in only one of the images due to considerable changes in scene between the times
the images were taken, there are landmarks that exist in both images. The algorithm is capable of finding the correspondence
between landmarks in such images and register the images. Registration of the images by an affine transformation (see the
auto affine registration page for details) using the obtained set of correspondences is shown in the left image in the bottom
row. Subtracting the registered images we obtain the right image in the bottom row, showing scene changes occurred
between the times the images were obtained.
To obtain a license for this software, please follow the link =>
Fig. 1. (Top row) Temporal Landsat images. These images are courtesy of NASA. (Bottom left) Registered images. (Bottom right)
Absolute difference of registered images.
Absolute difference of registered images.
