Coercive region-level registration for multi-modal images

@article{Chen2015CoerciveRR,
  title={Coercive region-level registration for multi-modal images},
  author={Yu-Hui Chen and Dennis L. Wei and G. Newstadt and J. Simmons and A. Hero},
  journal={2015 IEEE International Conference on Image Processing (ICIP)},
  year={2015},
  pages={2419-2423}
}
We propose a coercive approach to simultaneously register and segment multi-modal images which share similar spatial structure. Registration is done at the region level to facilitate data fusion while avoiding the need for interpolation. The algorithm performs alternating minimization of an objective function informed by statistical models for pixel values in different modalities. Hypothesis tests are developed to determine whether to refine segmentations by splitting regions. We demonstrate… Expand
Statistical estimation and clustering of group-invariant orientation parameters
Multimodal Image Fusion and Its Applications.

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