基于视觉单词选择的高分辨率遥感图像飞机目标检测

高分辨率遥感图像中飞机目标的检测和识别具有重要的军事和民用价值，针对以往方法易受灰度分布和形态变化及伪装干扰等缺点，提出一种基于视觉词袋模型的高分辨率遥感图像飞机目标检测的新方法。为了精简飞机视觉码本得到最具鉴别力的视觉单词，结合相关性及冗余度分析去除视觉码本中不相关、弱相关以及冗余的视觉单词，选择对飞机目标检测最为重要的视觉单词，减少了计算复杂度，提高了算法的检测性能。

Aircraft Detection in High-Resolution Remote Sensing Imagery Based on Visual Words Selection

It is difficult to detect the target of aircrafts in high resolution remote sensing images. So a bag of visual words model is proposed. In order to abtain the most discr imi native visual words and make visual codebook effective and compact, the visual w ords that are irrelevant, weakly irrelevant and redundant must be removed from t he visual codebook. The method integrating relevance analysis wit h redundancy analysis is used to prune out those useless visual words. Finally, t he most important visual words are chosen to describe aircrafts in high resoluti on remote sensing images, which helps reducing the computation in the following test stage and also improving the efficiency.