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The Role of Non-Overlap in Image Registration Jonas August and Takeo Kanade
 

Summary: The Role of Non-Overlap in Image Registration
Jonas August and Takeo Kanade
Healthcare Robotics Center, The Robotics Institute
Carnegie Mellon University, Pittsburgh, Pennsylvania
Abstract. Here we model the effect of non-overlapping voxels on image
registration, and show that a major defect of overlap-only models--their
limited capture range--can be alleviated. Theoretically, we introduce
a maximum likelihood model that combines histograms of overlapping
and non-overlapping voxels into a common joint distribution. The con-
vex problem for the joint distribution is solved via iterative application
of replicator equations that converge monotonically. We then focus on
rigidly aligning images with unknown translation, where we present a
fast FFT-based method for computing joint histograms for all relative
translations of an image pair. We then apply this method to standard
overlap-only information theoretic registration criteria such as mutual
information as well as to our variants that exploit non-overlap. Our ex-
perimental results show that global optima correspond to the correct
registration generally only when non-overlapping image regions are in-
cluded.
1 Introduction

  

Source: August, Jonas - Robotics Institute, School of Computer Science, Carnegie Mellon University

 

Collections: Engineering; Chemistry