基于Bayes融合法的多源遥感影像分类

Multisource Classification of Remotely Sensed Data Based on Bayesian Data Fusion Method

  • 摘要: 提出了顾及各数据源成像模型、上下文关系模型和可靠性的基于Bayes融合分类的方法,并采用该方法对Landsat TM和航空SAR影像进行土地利用分类试验。结果表明:同单独SAR影像分类结果相比,融合分类法将分类精度提高了20%。

     

    Abstract: In this paper, a new method for classification of multisource data is proposed. The images formation model, contextual model and reliability factors are taken into account in the method. The performance of the method is evaluated by fusing Landsat TM images and SAR image for land-use classification. Significant improvements in classification accuracy compared to the SAR image classifier are obtained. So it is an effective and robust method for multisource classification of remotly sensed data.

     

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