| SAR与TM影像融合及在BP神经网络分类中的应用 |
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| 引用本文： | 张海龙,蒋建军,吴宏安,解修平.SAR与TM影像融合及在BP神经网络分类中的应用[J].测绘学报,2006,35(3):229-233,239. |
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| 作者姓名： | 张海龙 蒋建军 吴宏安 解修平 |
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| 作者单位： | 南京师范大学,地理科学学院,江苏,南京,210097;中国科学院,地球环境研究所,陕西,西安,710075 |
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| 基金项目： | SustainableAgroecosystemManagementandDevelopmentofRural-UrbanInteractioninregionsandcitiesofChina(SUSDEV-CHINA)(ICA4-CT-2002-10004) |
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| 摘 要： | 以加拿大Radarsat SAR与美国Landsat TM影像为信息源,分别将SAR与TM影像的DN值转换为表征地物特征的后向散射系数和反射率,利用改进的SVR法进行融合,同时与HIS,Brovey以及小波变换的融合效果作定量比较,并利用优化的BP神经网络模型,以相同的训练区分别对融合前后的影像进行监督分类。结果表明:改进的SVR法融合影像的光谱信息保持性、信息量以及分类精度都优于常用的融合方法,且分类精度比TM影像有较大提高。
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| 关 键 词： | 融合 TM SAR BP神经网络分类 |
| 文章编号： | 1001-1595（2006）03-0229-05 |
| 收稿时间： | 2005-08-23 |
| 修稿时间： | 2005-08-232006-03-29 |
The BP Neural Network Classification Based on the Fusion of SAR and TM Images |
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| ZHANG Hai-long,JIANG Jian-jun,WU Hong-an,XIE xiu-ping.The BP Neural Network Classification Based on the Fusion of SAR and TM Images[J].Acta Geodaetica et Cartographica Sinica,2006,35(3):229-233,239. |
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| Authors: | ZHANG Hai-long JIANG Jian-jun WU Hong-an XIE xiu-ping |
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| Abstract: | The Radar SAR and Landsat TM images are selected as the experimental datum,after converting the DN value to backscatter coefficient and reflectance respectively,the improved SVR method is used to fuse the data.To compare with fusion result,the HIS,brovey and wavelet method are used in this article.Finally,the optimized back propagation model is used to classify the TM and the fusion images with the same training areas.The experiment results are analyzed in spectrum maintenance or in quantity and the accuracy of the classification,it shows that the improved SVR fusion method is superior to other commonly used fusion methods. |
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| Keywords: | fusion TM SAR BP neural network classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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