Name
Abstract | ||
|---|---|---|
A new technique is described for the registration of edge-detected images. While an extensive literature exists on the problem of image registration, few of the current approaches include a well-defined measure of the statistical confidence associated with the solution. Such a measure is essential for many autonomous applications, where registration solutions that are dubious (involving poorly focused images or terrain that is obscured by clouds) must be distinguished from those that are reliable (based on clear images of highly structured scenes). The technique developed herein utilizes straightforward edge pixel matching to determine the "best” among a class of candidate translations. A well-established statistical procedure, the McNemar test, is then applied to identify which other candidate solutions are not significantly worse than the best solution. This allows for the construction of confidence regions in the space of the registration parameters. The approach is validated through a simulation study and examples are provided of its application in numerous challenging scenarios. While the algorithm is limited to solving for two-dimensional translations, its use in validating solutions to higher-order (rigid body, affine) transformation problems is demonstrated. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TPAMI.2007.3 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | DocType | Volume |
affine transformation,statistical analysis,feature detection,computer vision,uncertainty analysis,uncertainty,image registration,nonparametric statistics,rigid body,confidence region,fuzzy,edge detection,higher order,probabilistic reasoning,binary image | Journal | 29 |
Issue | ISSN | Citations |
1 | 0162-8828 | 19 |
PageRank | References | Authors |
0.90 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Katherine M. Simonson | 1 | 20 | 1.25 |
| Steven M. Drescher | 2 | 19 | 0.90 |
| Franklin R. Tanner | 3 | 19 | 0.90 |