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ＬａｎｄｓａｔＴＭ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％。
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.
出处
《武汉测绘科技大学学报》
CSCD
1997年第3期248-251,共4页
Geomatics and Information Science of Wuhan University
基金
测绘遥感信息工程国家重点实验室开放研究基金
关键词
Bayes融合法
多源遥感
影像分类
遥感
Bayesian fusion method
autoregressive random field
contextual information
multisource classification of remotely sensed data
