【摘要】 传统的光电成像跟踪系统中,通常采用固定尺度的滤波器对图像中的小目标进行检测。由于目标与系统距离的改变,通常会带来其成像特征尤其是大小的不断变化,这种特点导致传统的固定尺度检测器难以适应目标大小的改变,无法获得最优的提取结果。针对这一问题,提出了一种尺度自适应的小目标检测方法。基于拉普拉斯尺度空间理论,利用对尺度归一化的拉普拉斯图像的分析,达到了目标信号增强的同时抑制背景杂波的效果,分别在空间与尺度上求得了最优的目标特征参数,完成了对不同尺度最优的小目标检测。通过仿真与外场试验表明,该方法显著提高了系统对小目标尤其是大小不断变化目标的检测能力。更多还原

【Abstract】 In the traditional photoelectric tracking system, the fixed scale filter is usually used for target detection. The target features especially the target size is changing all the time due to the distance change between the target and tracking system. It results in the filter not suitable for the target size changing, and it is difficult for the system to obtain the best extraction results. For this question, a small target detection method based on adaptive scale is proposed. Based on the Laplacian scale-space theory, the normalized Laplacian scale-space images are studied, the target signal is enhanced and the noise is suppressed at the same time. By finding the best parameter of target both in the scale and space, the small targets with different scale could be detected effectively. The simulation test and the experimental results show that the method proposed improved the detection capability of the system for small target with different size remarkably.更多还原