Solution of multiple-point statistics to extracting information from remotely sensed imagery
文献类型：SCI/SSCI论文
| 作者 | Ge Y. |
| 发表日期 | 2008 |
| 关键词 | information extraction spectral information spatial information multiple-point statistics |
| 英文摘要 | Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier (MLC). |
| 出处 | Journal of China University of Geosciences |
| 卷 | 19 |
| 期 | 4 |
| 页 | 421-428 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1002-0705 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/23953]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Ge Y.. Solution of multiple-point statistics to extracting information from remotely sensed imagery. 2008. |
入库方式： OAI收割
来源：地理科学与资源研究所
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