Enhanced Subpixel Mapping With Spatial Distribution Patterns of Geographical Objects
文献类型：SCI/SSCI论文
| 作者 | Ge Y.; Chen, Y. H.; Stein, A.; Li, S. P.; Hu, J. L.; Yang, L.
|
| 发表日期 | 2016 |
| 关键词 | Classification mixed pixel remotely sensed images spatial distribution patterns of geographical objects subpixel mapping (SPM) markov-random-field remote-sensing imagery shifted hyperspectral imagery sub-pixel scales sensed imagery map model regularization quantification constraints algorithms |
| 英文摘要 | This paper proposes spatial distribution pattern based subpixel mapping (SPMs) as a novel subpixel mapping (SPM) strategy. It separately considers spatial distribution patterns of different types of geographical objects. Initially, it classifies geographical objects into areal, linear, and point patterns according to their spatially geometric characteristics. For the different patterns, SPMs uses the vectorial boundary -based SPM algorithm with the spatial dependence assumption to deal with areal objects, the linear template matching-based SPM algorithm for linear objects, and the spatial pattern consistency matching -based SPM algorithm for point objects. The three patterns are integrated to generate a subpixel map. An artificially created image and two remotely sensed images were used to evaluate the performance of SPMs. The results were compared with a traditional hard classifier and seven existing SPM methods. The experimental results demonstrated that SPMs performed better than the hard classification and traditional SPM methods, particularly when dealing with linear and point objects. |
| 出处 | Ieee Transactions on Geoscience and Remote Sensing |
| 卷 | 54 |
| 期 | 4 |
| 页 | 2356-2370 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 0196-2892 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/43233]  |
| 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.,Chen, Y. H.,Stein, A.,et al. Enhanced Subpixel Mapping With Spatial Distribution Patterns of Geographical Objects. 2016. |
入库方式： OAI收割
来源：地理科学与资源研究所
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