DMCA
An efficient mutual information optimizer for multiresolution image registration (1998)
| Venue: | In Proceedings of the 1998 IEEE International Conference on Image Processing (ICIP’98), volume I |
| Citations: | 16 - 0 self |
BibTeX
@INPROCEEDINGS{Unser98anefficient,
author = {Michael Unser},
title = {An efficient mutual information optimizer for multiresolution image registration},
booktitle = {In Proceedings of the 1998 IEEE International Conference on Image Processing (ICIP’98), volume I},
year = {1998},
pages = {833--837}
}
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Abstract
We propose a new optimizer in the context of multimodal image registration. The optimized criterion is the mutual in-formation between the images to align. This criterion requires that their joint histogram be available. For its computation, we introduce differentiable and separable Parzen windows that satisfy the partition of unity. Along with a continuous model of the images based on splines, this allows us to derive exact and tractable expressions for the gradient and the Hessian of the criterion. Then, we develop an optimizer based on the Marquardt-Levenberg strategy. Our new optimizer is specific to mutual information, in the same sense that Marquardt-Levenberg is specific to least-squares. We show that our optimizer is particularly well-adapted to an iterative coarse-to-fine approach. We validate its accuracy by comparing its performance to that of several results avail-able in the literature. 1.
Keyphrases
efficient mutual information optimizer multiresolution image registration new optimizer tractable expression iterative coarse-to-fine approach mutual information marquardt-levenberg strategy optimized criterion mutual in-formation several result continuous model multimodal image registration separable parzen window joint histogram
