Remote sensing image classification is the basis of remote sensing image analysis and understanding.It aims to assign each pixel an object class label.To achieve satisfactory classification accuracy,single feature is ...Remote sensing image classification is the basis of remote sensing image analysis and understanding.It aims to assign each pixel an object class label.To achieve satisfactory classification accuracy,single feature is not enough.Multiple features are usually integrated in remote sensing image classification.In this paper,a method based on neural network to combine multiple features was proposed.A single network was used to perform the task instead of ensemble of neural networks.A special architecture of network was designed to fit the task.The method effectively avoids the problems in direct conjunction of multiple features.Experiments on Indian93 data set show that the method has obvious advantages over conjunction of features on both recognition rate and training time.展开更多
基金National Natural Science Foundation of China(No.61101202)
文摘Remote sensing image classification is the basis of remote sensing image analysis and understanding.It aims to assign each pixel an object class label.To achieve satisfactory classification accuracy,single feature is not enough.Multiple features are usually integrated in remote sensing image classification.In this paper,a method based on neural network to combine multiple features was proposed.A single network was used to perform the task instead of ensemble of neural networks.A special architecture of network was designed to fit the task.The method effectively avoids the problems in direct conjunction of multiple features.Experiments on Indian93 data set show that the method has obvious advantages over conjunction of features on both recognition rate and training time.
