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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Creating Multi-layered 3D Images Using Reversible Jump MCMC Algorithms
verfasst von : Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J. Gibson
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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Standard 3D ranging and imaging systems process only a single return from an assumed single opaque surface. However, there are situations when the laser return consists of multiple peaks due to the footprint of the beam impinging on a target with surfaces distributed in depth or with semi-transparent surfaces. If all these returns are processed, a more informative multi-layered 3D image is created. We propose a unified theory of pixel processing for ladar data using a Bayesian approach that incorporates spatial constraints through a Markov Random Field. The different parameters of the several returns are estimated using reversible jump Markov chain Monte Carlo (RJMCMC) techniques in combination with an adaptive strategy of delayed rejection to improve the estimates of the parameters.