Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a mapping procedure exploiting object boundaries in very high-resolution (VHR) images is proposed. After discrimination beten boundary and nonboundary pixel sets, each of the two sets is separately classified. The former are labeled using a neural network (NN), and the shape of the pixel set is finely tuned by enforcing a few geometrical constraints, while the latter are classified using an adaptive Markov random field (MRF) model. The two mapping outputs are finally combined through a decision fusion process. Experimental results on hyperspectral and satellite VHR imagery show the superior performance of this method over conventional NN and MRF classifiers.
['Paolo Gamba', 'F. Dell’Acqua', 'Gianni Lisini', 'Giovanna Trianni']
I am writing a research paper on a idea Improved VHR Urban Area Mapping Exploiting Object Boundaries
[{"from": "human", "value": "I am writing a research paper on a idea Improved VHR Urban Area Mapping Exploiting Object Boundaries"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a mapping procedure exploiting object boundaries in very high-resolution (VHR) images is proposed. After discrimination beten boundary and nonboundary pixel sets, each of the two sets is separately classified. The former are labeled using a neural network (NN), and the shape of the pixel set is finely tuned by enforcing a few geometrical constraints, while the latter are classified using an adaptive Markov random field (MRF) model. The two mapping outputs are finally combined through a decision fusion process. Experimental results on hyperspectral and satellite VHR imagery show the superior performance of this method over conventional NN and MRF classifiers."}]