An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model
文献类型：EI期刊论文
| 作者 | Chen Baozhang |
| 发表日期 | 2013 |
| 关键词 | Reflection Image fusion Natural resources management Satellite imagery |
| 英文摘要 | High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these models' capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent. 2013 by the authors; licensee MDPI, Basel, Switzerland. |
| 出处 | Remote Sensing
 |
| 卷 | 5期:12页:6346-6360 |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/31249]  |
| 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 | Chen Baozhang. An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model. 2013. |
入库方式： OAI收割
来源：地理科学与资源研究所
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