中文摘要：

提出一种结合视觉显著性和空间金字塔的遥感图像机场检测方法，首先根据改进的直线段检测算法对滑动窗口进行目标存在初步判断，只对可能含有目标的窗口按照空间金字塔表示方法提取该窗口中每一图像子块的稀疏编码，利用基于视觉显著性的特征抽取策略形成表征滑动窗口的全局特征向量，然后对该特征向量进行分类判别，得到滑动窗口含有目标的置信值，最后采用非极大值抑制完成机场检测。实验结果表明，该机场检测方法相比其他方法检测效率显著提高，并且具有识别率高、虚警率低的特点。

英文摘要：

We use the improved line segment detector algorithm to judge preliminarily whether the sliding window contains an airport or not. Then we use the spatial pyramid feature expression method based on visual saliency to ex- tract the sparse coding of each image patch in the sliding window that may contain the airport. The global feature vector that characterizes the sliding window is formed by using the visual saliency-based feature extraction strategy and then classified and judged by the support vector machine to distinguish the airport image from background im- age, thus obtaining the confidence values of the sliding window that contains the airport. Finally we use the non- maximum suppression method to detect the airport image. The simulation results, given in Table 1, show prelimina- rily that our airport detection method can robustly express the sliding window and effectively detect the airport im- age, has a higher detection rate and smaller false alarm rate the other airport detection methods.