| 遥感融合图像分类精度的研究 |
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| 引用本文： | 吴连喜. 遥感融合图像分类精度的研究[J]. 计算机工程与应用, 2003, 39(36): 48-51 |
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| 作者姓名： | 吴连喜 |
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| 作者单位： | 东华理工学院测量系,江西,抚州,344000 |
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| 基金项目： | 国家留学基金资助(编号:2003836044) |
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| 摘 要： | 把不同空间分辨率的TM和IRS遥感图像进行融合,综合了不同传感器数据所提供的信息,增强了图像的清晰度,改善了解译效果。对遥感融合图像进行分类,分类精度达97.90%,效果优于TM图像(分类精度为89.39%)。
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| 关 键 词： | 遥感 融合 分类 |
| 文章编号： | 1002-8331-(2003)36-0048-04 |
| 修稿时间： | 2003-10-01 |
Study of Classification Accuracy of RS Fused Image |
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| Wu Lianxi. Study of Classification Accuracy of RS Fused Image[J]. Computer Engineering and Applications, 2003, 39(36): 48-51 |
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| Authors: | Wu Lianxi |
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| Abstract: | The fused remote sensing image could merge two optical image data of different resolutions-a high spatial resolution panchromatic image and a low spatial resolution multi-spectral image.It could synthesize information from dif-ferent remote sensor.The sign may be strengthened in the fused image.The classification Accuracy based on the multi-layer perception neural networks for the fused RS image is higher than TM image.The classification accuracy for the fused RS image is up to97.90%,the accuracy of TM image is89.39%. |
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| Keywords: | Remote Sensing Fusion Classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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