| Semi-auto nonrigid multimodality registration |
| Image Registration and Fusion Systems |
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To combine information in two or more images of a scene obtained by different sensors, the images must first be registered. A
number of similarity measures (mutual information, entropy, and energy) are provided for determining the similarity between local
neighborhoods in the images, thus establishing correspondence between the images. From the corresponding points, a surface
spline transformation is then determined to register the images.
Image registration steps
Registration is guided by the user. The user first interactively selects a small number of corresponding points in the images.
Typically, 2 or 3 correspondences are sufficient. The user then uses a pull-down menu to transform the geometry of one image to
that of another image using the selected correspondences. The user next directs the system to find a larger number of
correspondences automatically using a pull-down menu. The correspondences found by the system are displayed, giving the
user the chance to remove the inaccurate ones. The correspondences found are then used to register the images more
accurately. If the registration accuracy is found insufficient, the user can direct the system to choose more correspondences and
register the images. This process can be repeated until a satisfactory registration is obtained..
Examples
Examples of image registration by this software are given below.
number of similarity measures (mutual information, entropy, and energy) are provided for determining the similarity between local
neighborhoods in the images, thus establishing correspondence between the images. From the corresponding points, a surface
spline transformation is then determined to register the images.
Image registration steps
Registration is guided by the user. The user first interactively selects a small number of corresponding points in the images.
Typically, 2 or 3 correspondences are sufficient. The user then uses a pull-down menu to transform the geometry of one image to
that of another image using the selected correspondences. The user next directs the system to find a larger number of
correspondences automatically using a pull-down menu. The correspondences found by the system are displayed, giving the
user the chance to remove the inaccurate ones. The correspondences found are then used to register the images more
accurately. If the registration accuracy is found insufficient, the user can direct the system to choose more correspondences and
register the images. This process can be repeated until a satisfactory registration is obtained..
Examples
Examples of image registration by this software are given below.
Fig. 1. (Top row) Images showing ISS and ASTER images of the New York City. Two corresponding control points are interactively
selected as shown by the circular regions. The centers of the circles correspond to each other. The circular regions are used as
templates to refine the correspondences automatically. (Bottom left) Image showing registration using these two
correspondences. (Bottom right) Result when additional correspondences are automatically determined and used to register the
images.
selected as shown by the circular regions. The centers of the circles correspond to each other. The circular regions are used as
templates to refine the correspondences automatically. (Bottom left) Image showing registration using these two
correspondences. (Bottom right) Result when additional correspondences are automatically determined and used to register the
images.
To obtain a license for this software, follow this link =>
| Fig. 2. Registration of radar and ISS images. The original IS, radar, and ASTER images are courtesy of NASA. |
