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Analysis and evaluation for the robustness of feature detection algorithm in medium-wave infrared scene

机译:中波红外场景中特征检测算法鲁棒性分析与评价

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Target recognition in natural scenes generally uses the remote sensing image preparation for the matching feature template. Image match system finds correspondence between real image and remote sensing image and then output the target position parameters to the aircraft. How to quantitative analysis and evaluate the robustness of the infrared features, and to determine the available features in infrared image matching recognition algorithm is one of the keys of the ground target recognition in complex scenes. In this paper, we built a feature robustness evaluation model for typical match identifying by analyzing for the robustness of features extracted from typical terrains and targets in various condition. Combined with France SE-Workbench-IR simulation platform, we designed a special scene simulation development process, in case of lack of terrain generation module, it also can generate MWIR natural scene image. By analyzing the simulation image and real-time image in the same condition, we can gain the variation information from infrared radiation characteristic in different natural condition. Finally, we verify and assess the robustness of the matching features.
机译:自然场景中的目标识别通常使用匹配特征模板的遥感图像准备。图像匹配系统在真实图像和遥感图像之间找到对应关系,然后将目标位置参数输出到飞机。如何定量分析和评估红外功能的鲁棒性,并确定红外图像匹配识别算法中的可用功能是在复杂场景中地面目标识别的键之一。在本文中,我们建立了一种稳定性评估模型,用于典型匹配,通过分析从各种情况下从典型地形和目标中提取的特征的鲁棒性分析。结合法国SE-Workbench-IR仿真平台,我们设计了一个特殊的场景仿真开发过程,在缺乏地形生成模块的情况下,它也可以生成MWIR自然场景图像。通过在同一条件下分析模拟图像和实时图像,我们可以在不同自然条件下从红外辐射特性获得变化信息。最后,我们验证并评估匹配功能的稳健性。

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