BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)

Optimization of Mutual Information for Multiresolution Image Registration

P. Thévenaz, M. Unser

IEEE Transactions on Image Processing, vol. 9, no. 12, pp. 2083-2099, December 2000.

We propose a new method for the intermodal registration of images using a criterion known as mutual information. Our main contribution is an optimizer that we specifically designed for this criterion. We show that this new optimizer is well adapted to a multiresolution approach because it typically converges in fewer criterion evaluations than other optimizers. We have built a multiresolution image pyramid, along with an interpolation process, an optimizer, and the criterion itself, around the unifying concept of spline-processing. This ensures coherence in the way we model data and yields good performance. We have tested our approach in a variety of experimental conditions and report excellent results. We claim an accuracy of about a hundredth of a pixel under ideal conditions. We are also robust since the accuracy is still about a tenth of a pixel under very noisy conditions. In addition, a blind evaluation of our results compares very favorably to the work of several other researchers.

Erratum

  • p. 2085, second column, third line, the numeric value for S is incorrect. It should read S ≅ −0.811 instead of S ≅ −0.865. 

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AUTHOR="Th{\'{e}}venaz, P. and Unser, M.",
TITLE="Optimization of Mutual Information for Multiresolution Image
	Registration",
JOURNAL="{IEEE} Transactions on Image Processing",
YEAR="2000",
volume="9",
number="12",
pages="2083--2099",
month="December",
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