中文摘要：

提出了一种从高分辨率全色卫星影像中提取车辆目标的形态神经网络方法．在这种方法中，使用了形态共享权神经网络（MSNN）把道路上的图像像素点集区分为车辆目标和非车辆目标．为了提高搜索效率和减少误检报警，还设计了一种形态预处理算法来获取候选兴趣域．文中采用0．6m分辨率的QuickBird全色数据进行了实验，实验结果表明提出的方法具有较好的检测性能．

英文摘要：

This paper introduces a morphological neural network approach to extract vehicle targets from high resolution panchromatic satellite imagery. In the approach, the morphological shared-weight neural network （MSNN） is used to classify image pixels on roads into vehicle targets and non-vehicle targets. In order to speed up the processing, a morphological preprocessing algorithm is developed to identify candidate vehicle pixels. Experiments on 0.6 meter resolution QuickBird panchromatic data are reported in this paper. The experimental results show that the proposed method has a good detection performance.