一种高分辨率遥感图像目标自动提取方法

吴波; 刘嘉; 王宏琦; 吴一戎

doi:10.3724/SP.J.1146.2007.00707

一种高分辨率遥感图像目标自动提取方法

doi: 10.3724/SP.J.1146.2007.00707

吴波^{①③　刘嘉,},
刘嘉,
王宏琦,
吴一戎

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- 被引次数: 0
出版历程
- 收稿日期: 2007-05-10
- 修回日期: 2007-08-15
- 刊出日期: 2008-11-19

A Method for Automatic Object Extraction in High-resolution Remote Sensing Image

Wu Bo^{①③　刘嘉
,},
Liu Jia,
Wang Hong-Qi,
Wu Yi-Rong

摘要

摘要: 该文提出一种高分辨率遥感图像目标自动提取方法，该方法首先使用分类器实现目标的快速检测，然后利用图像色彩模型和平滑性先验知识建立分割代价函数，并最小化此代价函数实现目标的精确提取，最后在后处理步骤中加入目标的形状先验知识，进一步提高精度。以油罐提取为例进行了实验，结果证明了该方法的有效性和鲁棒性。
- Adaboost /
- 有监督学习 /
- 高斯混合模型 /
- EM(Expectation Maximization)算法 /
- 目标提取
Abstract: In this paper, a method for automatic object extraction in high-resolution remote sensing image is proposed. First, a robust multilayer classifier is employed to detect the object efficiently. Secondly, a cost function based on the color model and the smoothness prior knowledge is built up and minimized to segment the object accurately. Lastly, in the post processing stage, the shape prior knowledge of the object is utilized to eliminate the false positives and improve the extraction precision. As an example of objects in remote sensing images the oil tanks are extracted. Experimental results demonstrate the robustness and effectiveness of the proposed automatic object extraction method.
- A /
- d /
- a /
- b

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参考文献(1)

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