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We describe a technique for the registration of images that relies on a statistical confidence measure. While an extensive literature exists on the problem of image registration, few of the current approaches include a well-defined measure of the confidence associated with the solution. Having a confidence measure is critical for many autonomous applications, where erroneous registration solutions can have a significant impact. Our method utilizes a cross-correlation based registration algorithm to determine the “best” among a class of candidate solutions. A statistical test is used to identify which other solutions are not significantly worse than the best solution. This allows for the construction of confidence regions.
This presentation is part of Minisymposium “MS3 - Applications of Imaging Modalities beyond the Visible Spectrum (2 parts)”
organized by: Max Gunzburger (Florida State University) , G-Michael Tesfaye (Naval Surface Warfare Center, Panama City) , Janet Peterson (Florida State University) .