基于模糊ARTMAP神经网络模型的遥感影像亚像元定位

基金项目: 国家863计划资助项目(2007AA12Z160)；国家自然科学基金资助项目(40672205)

详细信息

Sub-pixel Mapping of Remote Sensing Images Based on Fuzzy ARTMAP Neural Network Model

¹China University of Geosciences,388 Lumo Road,Wuhan 430074,China;²State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,129 Luoyu Road,Wuhan 430079,China

Funds: 国家863计划资助项目(2007AA12Z160)；国家自然科学基金资助项目(40672205)

摘要: 结合亚像元的相关理论,提出了基于模糊ARTMAP神经网络模型的遥感影像亚像元定位方法,利用该方法对模拟的武汉地区的TM影像进行了实验,并将实验结果与BP神经网络模型进行了比较。结果证明,利用本文方法能够更有效地解决亚像元定位的问题。
- 遥感分类 /
- 混合像元 /
- 亚像元定位 /
- 模糊ARTMAP
Abstract: A fuzzy ARTMAP model is proposed to solve the problem of sub-pixel mapping with the assumption of spatial dependence,based on the assumption of spatial dependence and the application of the soft classification result.The model was tested on synthetic TM image in Wuhan area.The result is compared with the result from BP,which shows that this method can efficiently resolve the problem of sub-pixel mapping.
- remote sensed classification /
- mixed pixel /
- sub-pixel mapping /
- fuzzy ARTMAP