An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is parti...An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.展开更多
At present,coal mine fires were forecasted with some temperature,smog,CO,CO_2,etc,however,this method can't meet the requirements for safe production of coalmines in monitoring accuracy and validity.Overcoming the...At present,coal mine fires were forecasted with some temperature,smog,CO,CO_2,etc,however,this method can't meet the requirements for safe production of coalmines in monitoring accuracy and validity.Overcoming these problems of foregone moni-toring methods,using multi-parameters which include fire image,smog,CO,CO_2,O_2,etc,the paper put forward a synthetical analysis monitor with advanced technology of neuralnetwork.The research and application of this method has significance in theory and prac-tical value for coal mine fire forecast.展开更多
文摘An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.
基金Supported by Special Funded Project on PhD Subject for Colleges(20050290010)
文摘At present,coal mine fires were forecasted with some temperature,smog,CO,CO_2,etc,however,this method can't meet the requirements for safe production of coalmines in monitoring accuracy and validity.Overcoming these problems of foregone moni-toring methods,using multi-parameters which include fire image,smog,CO,CO_2,O_2,etc,the paper put forward a synthetical analysis monitor with advanced technology of neuralnetwork.The research and application of this method has significance in theory and prac-tical value for coal mine fire forecast.
