We present a new algorithm for mutual information estimation for image registration based on the nearest neighbor entropy estimator of Kozachenko and Leonenko. We modify the algorithm to be numerically robust and computationally efficient, with optimal asymptotic complexity O(N/sub pixels/d/sub dim/). We propose two MI-based criteria exploiting the high-dimensionality of the feature space and show their effectiveness in determining the correct alignment even in difficult cases when classical criteria fail.
High-dimensional mutual information estimation for image registration
Published 2004 in 2004 International Conference on Image Processing, 2004. ICIP '04.
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- Publication year
2004
- Venue
2004 International Conference on Image Processing, 2004. ICIP '04.
- Publication date
2004-10-24
- Fields of study
Mathematics, Computer Science
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