| TM和SAR遥感图像的不同层次融合分类比较 |
| |
| 引用本文： | 于秀兰,钱国蕙. TM和SAR遥感图像的不同层次融合分类比较[J]. 遥感技术与应用, 1999, 14(3): 38-43. DOI: 10.11873/j.issn.1004-0323.1999.3.38 |
| |
| 作者姓名： | 于秀兰 钱国蕙 |
| |
| 作者单位： | 哈尔滨工业大学航天电子与光电工程系,哈尔滨,150001 |
| |
| 摘 要： | 多传感器遥感图像为分类技术提供了更多的地物特征信息，有助于提高分类精度，增强计算机自动解译的能力，减少遥感图像的后处理时间。给出了ＴＭ 和ＳＡＲ遥感图像根据信息处理所在的不同层次融合分类特征的选取及分类方法，并从融合分类的精度和计算时间消耗上对哈尔滨市附近地区５１２×５１２ 大小的ＴＭ和ＪＥＲＳ１ 的ＳＡＲ图像的不同层次融合的分类进行比较，指出特征层融合是ＴＭ和ＳＡＲ遥感图像融合分类的最理想层次
|
| 关 键 词： | 遥感图像 融合 分类 |
| 文章编号： | 1004-0323(1999)03-0038-06 |
| 修稿时间： | 1999-05-28 |
Comparison of TM and SAR Remote Sensing Image Different Level Fusion Classification Effect |
| |
| YU Xiu-lan,QIAN Guo-hui. Comparison of TM and SAR Remote Sensing Image Different Level Fusion Classification Effect[J]. Remote Sensing Technology and Application, 1999, 14(3): 38-43. DOI: 10.11873/j.issn.1004-0323.1999.3.38 |
| |
| Authors: | YU Xiu-lan QIAN Guo-hui |
| |
| Affiliation: | (Dept. of Astronautic Electronics & Opto Electronic Engineering, Harbin Institute of Technology,Haerbin, 150001) |
| |
| Abstract: | Multi sensor remote sensing image fusion technique provides more information of ground objects to classification than single sensor image. And it is helpful to improve classified accuracy, enhance computer automatic interpreting capability, and reduce the remote sensing image postprocessing time. The characters selection and classified method of TM and SAR remote sensing image different level fusion are given in this paper, and the different level fusion classified results of 512×512 TM and JERS |
| |
| Keywords: | Remote sensing image Fusion Classification |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《遥感技术与应用》浏览原始摘要信息 |
|
点击此处可从《遥感技术与应用》下载免费的PDF全文 |
