| Automatic Nonrigid Registration |
| Image Registration and Fusion Systems |
Often the images to be registered have nonlinear geometric differences, requiring a nonlinear transformation to register them. A
three-step automatic algorithm has been developed by Image Registration and Fusion Systems to register such images. The
algorithm follows these steps:
method can handle local geometric differences but the differences should vary gradually. The method may not produce accurate
results when images have sharp local geometric differences.
Examples of image registration by this software are given below. The images in Figs. 1a and 1b represent two aerial
photographs of the New York City taken in 1966 at scale of 1:24,000. Image geometric differences exist due to lens nonlinearity
and film distortions. These images are courtesy of NASA. Using the images as input to the automatic nonrigid registration
software, first the images are automatically registered by the affine transformation using three corresponding control points in the
images. This result is shown in Fig. 1c. A dozen corresponding control points are then automatically selected from the registered
images. From the correspondences, the parameters of a surface spline are obtained to elastically register the images. The
elastic registration result is shown in Fig. 1d. The user may now require the software to choose a larger number of
correspondences to improve the registration accuracy. By the press of a mouse button, the program automatically selects a
larger number of control point correspondences in the images and registers the images. Fig. 1e shows registration using 39
control point correspondences.
A larger number of correspondences does not necessarily mean a more accurate registration. As more control points are
selected, the likelihood of obtaining inaccurate correspondences increases, and that could reduce the overall registration
accuracy. The program, however, can detect this and stop the process. The program works ideally when the images do not have
intensity differences. The process that stops the registration will become less reliable as intensity differences between the
images increase.
A second example is given in Fig. 2. The images to be registered are given in Figs. 2a and 2b and the result after the affine
registration is shown in Fig. 2c. Ten control point correspondences are used to find the affine parameters. The number of control
points selected in each step is image dependent. When more than three control points are found, a process selects the best
three to maximize accuracy in affine registration. The result of nonrigid registration using 19 control points is shown in Fig. 2d.
Again, the number of control points selected and used in nonrigid registration is image dependent. Asking the program to select
and use more control points in these images actually reduces the registration accuracy due to the rather sharp local geometric
differences between the images, Therefore, the process stops after initial nonrigid registration.
This software is suitable for registering aerial images. The software is also suitable for registering biomedical images where
intensity differences between the images are small, occlusion is rare in the images, and local geometric differences between the
images are very small.
For more information about this automatic nonrigid registration software contact Image Registration and Fusion Systems.
three-step automatic algorithm has been developed by Image Registration and Fusion Systems to register such images. The
algorithm follows these steps:
- It select a small number of corresponding landmarks in the images and from the correspondences determines the
parameters of an affine transformation to approximately registers the images. - It then select a larger number of landmark correspondences in the approximately registered images and from the
correspondences determine the parameters of a surface spline to register the images more accurately. - Step 2 may be repeated as needed to increase the registration accuracy.
method can handle local geometric differences but the differences should vary gradually. The method may not produce accurate
results when images have sharp local geometric differences.
Examples of image registration by this software are given below. The images in Figs. 1a and 1b represent two aerial
photographs of the New York City taken in 1966 at scale of 1:24,000. Image geometric differences exist due to lens nonlinearity
and film distortions. These images are courtesy of NASA. Using the images as input to the automatic nonrigid registration
software, first the images are automatically registered by the affine transformation using three corresponding control points in the
images. This result is shown in Fig. 1c. A dozen corresponding control points are then automatically selected from the registered
images. From the correspondences, the parameters of a surface spline are obtained to elastically register the images. The
elastic registration result is shown in Fig. 1d. The user may now require the software to choose a larger number of
correspondences to improve the registration accuracy. By the press of a mouse button, the program automatically selects a
larger number of control point correspondences in the images and registers the images. Fig. 1e shows registration using 39
control point correspondences.
A larger number of correspondences does not necessarily mean a more accurate registration. As more control points are
selected, the likelihood of obtaining inaccurate correspondences increases, and that could reduce the overall registration
accuracy. The program, however, can detect this and stop the process. The program works ideally when the images do not have
intensity differences. The process that stops the registration will become less reliable as intensity differences between the
images increase.
A second example is given in Fig. 2. The images to be registered are given in Figs. 2a and 2b and the result after the affine
registration is shown in Fig. 2c. Ten control point correspondences are used to find the affine parameters. The number of control
points selected in each step is image dependent. When more than three control points are found, a process selects the best
three to maximize accuracy in affine registration. The result of nonrigid registration using 19 control points is shown in Fig. 2d.
Again, the number of control points selected and used in nonrigid registration is image dependent. Asking the program to select
and use more control points in these images actually reduces the registration accuracy due to the rather sharp local geometric
differences between the images, Therefore, the process stops after initial nonrigid registration.
This software is suitable for registering aerial images. The software is also suitable for registering biomedical images where
intensity differences between the images are small, occlusion is rare in the images, and local geometric differences between the
images are very small.
For more information about this automatic nonrigid registration software contact Image Registration and Fusion Systems.
(a)
(b)
(c)
(d)
(e)
Fig. 1. (a), (b) Aerial photographs of the New York City taken in 1966. These images are courtesy of NASA. Image (b) has been
rotated by 90 degrees from its original orientation to increase the global geometric difference between the images. (c) The
registration result after the affine registration. (d) The result after the initial nonrigid registration. (e) The result after repeating
the nonrigid registration one more time using a larger number of control point correspondences.
rotated by 90 degrees from its original orientation to increase the global geometric difference between the images. (c) The
registration result after the affine registration. (d) The result after the initial nonrigid registration. (e) The result after repeating
the nonrigid registration one more time using a larger number of control point correspondences.
(a)
(b)
(c)
(d)
Fig. 2. (a), (b) Two images of an outdoor scene taken from slightly different views. (c) Affine registration result. (d) Nonrigid
registration result.
registration result.
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To obtain a license for this automatic nonrigid image registration software, follow this link =>
