基于Bayes融合法的多源遥感影像分类

基金项目: 测绘遥感信息工程国家重点实验室开放研究基金资助项目。

详细信息

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%。
- Bayes融合法 /
- 自回归随机场 /
- 上下文信息 /
- 多源遥感影像分类
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.
- Bayesian fusion method /
- autoregressive random field /
- contextual information /
- multisource classification of remotely sensed data