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| Tree Crown Extraction Based on Data-Driven and Stochastic Diffusions |
| Lin Yin①②③ Li HengChao①②③ Hong Wen①② |
| ①(National Key Lab of Microwave Imaging Technology, Beijing 100190, China) ②(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China) ③(Graduate University of the Chinese Academy of Sciences, Beijing 100039, China) |
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Abstract Remote sensing imagery plays a key role in forestry management. The increasing availability of data and their high spatial resolution make the tree crown extraction necessary and possible. Marked point processes are employed to model the tree crowns, based on the characteristics of them. The parameters of the model are optimized by RJMCMC (Reversible Jump Markov Chain Monte Carlo sampler) and Simulate annealing. New data term is proposed to give better description of the local pattern of the tree crown; Data-driven Birth-and-Death and Stochastic Diffusions are introduced to reduce the complexity of RJMCMC kernel and accelerate convergence speed. The method is verified on remote sensing image.
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Received: 01 March 2007
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Corresponding Authors:
Lin Yin
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2008, Vol. 30 
