Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A valid multiscale classification method of synthetic aperture radar (SAR) imagery is proposed based on Multiscale technology and Markov Random Field (MRF) mode. Firstly,  employ multiscale autoregressive model for extracting the feature of SAR image. which is modeled by Markov Random Field (MRF) Model that relies on the Gaussian distribution. Secondly, using the joint probability distribution in terms of an energy function, estimation of parameters can be performed by the stochastic relaxation algorithm. Then the maximum posteriori (MAP) is designed as the optimal criterion and the final labels are obtained by the simulated annealing algorithm. Experimental results show that this method is accurate, efficient and robust.
['Xu Jiao', 'Xian-Bin Wen']
I am writing a research paper on a idea SAR Image Segmentation Based on Markov Random Field Model and Multiscale Technology
[{"from": "human", "value": "I am writing a research paper on a idea SAR Image Segmentation Based on Markov Random Field Model and Multiscale Technology"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A valid multiscale classification method of synthetic aperture radar (SAR) imagery is proposed based on Multiscale technology and Markov Random Field (MRF) mode. Firstly,  employ multiscale autoregressive model for extracting the feature of SAR image. which is modeled by Markov Random Field (MRF) Model that relies on the Gaussian distribution. Secondly, using the joint probability distribution in terms of an energy function, estimation of parameters can be performed by the stochastic relaxation algorithm. Then the maximum posteriori (MAP) is designed as the optimal criterion and the final labels are obtained by the simulated annealing algorithm. Experimental results show that this method is accurate, efficient and robust."}]