测绘学报

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基于空间自相关BP神经网络的遥感影像亚像元定位

许雄1,钟燕飞2,张良培2,李平湘2   

  1. 1. 武汉大学
    2. 武汉大学测绘遥感信息工程国家重点实验室
  • 收稿日期:2010-02-01 修回日期:2010-04-23 出版日期:2011-06-25 发布日期:2011-06-25
  • 通讯作者: 钟燕飞

A Sub-pixel Mapping Algorithm based on BP Neural Network with Spatial Autocorrelation Function for Remote Sensing

  • Received:2010-02-01 Revised:2010-04-23 Online:2011-06-25 Published:2011-06-25

摘要: 亚像元定位技术是一种获取地物在混合像元中分布信息的有效方法。本文提出了一种基于空间自相关函数的遥感影像BP神经网络亚像元定位方法,与传统的BP神经网路亚像元定位方法相比,该方法利用空间自相关函数Moran' I在亚像素级上对定位结果进行约束,其结果更符合空间相关性假设理论。实验结果表明,本文提出的方法优于传统BP神经网络亚像元定位方法,具有更高的定位精度。

Abstract: Sub-pixel mapping is an effective method to obtain the distribution of land cover in mixed pixels. This paper proposes a sub-pixel mapping algorithm based on an improved BP neural network with Moran' I, which is a kind of spatial autocorrelation function, to constrain the distribution of sub-pixels to satisfy the concept of spatial dependence better than conventional BP neural network methods. The experimental results indicate that the proposed mapping algorithm outperforms the original BPNN model in terms of both quantitative measurements and visual evaluation.