Simultaneous multi-modal registration of multiple images based on multi-dimensional joint phase moment distributions

Alexander Wong
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mlkexztp5vbdfo3nlsmbuf4oia" style="color: black;">Pattern Recognition (ICPR), Proceedings of the International Conference on</a> </i> &nbsp;
In this paper, a novel method for simultaneously registering multiple images acquired from different imaging modalities is presented. The optimal alignment is computed as the set of transformations that minimize the dispersion of the multi-dimensional joint phase moment distribution. Dispersion is measured as the cumulative quadratic orthogonal distance between samples from the joint phase moment distribution and the corresponding multi-dimensional fitted hyperline. The proposed method is
more &raquo; ... ed to be computationally efficient, robust to signal non-homogeneities and noise, and maintains internal consistency amongst all images. Experimental results using real-world medical and remote sensing images show that the proposed method achieves a high level of registration accuracy when simultaneously registering multiple multimodal images.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icpr.2008.4761912">doi:10.1109/icpr.2008.4761912</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icpr/Wong08.html">dblp:conf/icpr/Wong08</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tlillsfug5brtnqmyw7kgkv44m">fatcat:tlillsfug5brtnqmyw7kgkv44m</a> </span>
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