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Intensity-Based Robust Similarity for Multimodal Image Registration, International Journal of Computer Mathematics

Juan Du 1, 2 Songyuan Tang 1, 2 Tianzi Jiang 1, 3 Zhensu Lu 1, 4
1 LIAMA - Brain imaging
2 Opto-electronic Engineering
3 NLPR - National Laboratory of Pattern Recognition [Beijing]
4 School of Information Science and Engineering
Abstract : This paper proposes a new intensity-based similarity metric that can be used for the registration of multimodal images. It combines the robust estimation with both the forward and inverse transformation to reduce the negative effects of outliers in the images. For this purpose, we firstly employ the multiresolution technique to downsample the original images, then resort to the simulated annealing method to initialize the transformation parameters at the coarsest resolution. Finally the Powell method is utilized to obtain the optimal transformation parameters at each resolution. In our experiments, the new method is compared to other popular similarity measures, on the synthetic data as well as the real data, and the experimental results are encouraging.
Keywords : Multimodal registration Forward and inverse transform Robust estimation Multi-resolution technique Optimization
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Journal articles
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https://hal.inria.fr/inria-00123833
Contributor : Chine Publications Liama Connect in order to contact the contributor
Submitted on : Thursday, January 11, 2007 - 10:43:39 AM
Last modification on : Saturday, October 9, 2021 - 4:07:38 AM

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Juan Du, Songyuan Tang, Tianzi Jiang, Zhensu Lu. Intensity-Based Robust Similarity for Multimodal Image Registration, International Journal of Computer Mathematics. International Journal of Computer Mathematics, Taylor & Francis, 2006, International Journal of Computer Mathematics, 38 (1), pp.49-57. ⟨10.1080/00207160500112944⟩. ⟨inria-00123833⟩

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