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
Type de document :
Article dans une revue
International Journal of Computer Mathematics, Taylor & Francis, 2006, International Journal of Computer Mathematics, 38 (1), pp.49-57. 〈10.1080/00207160500112944〉
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https://hal.inria.fr/inria-00123833
Contributeur : Chine Publications Liama <>
Soumis le : jeudi 11 janvier 2007 - 10:43:39
Dernière modification le : mardi 24 avril 2018 - 13:51:23

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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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