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Target broker compression for multi-level fusion

机译:用于多层融合的目标代理压缩

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摘要

Information Fusion consists of low-level information fusion (LLIF) of object-level assessment which is subject to many operating conditions of the sensor type, environment conditions, and the targets. Likewise, high-level information fusion (HLIF) requires proactive management of sensor parameters. One example of a parameter that affects downstream information fusion tasks of target tracking and identification is that of upstream image compression. In this paper, we present a technique for analyzing the effects of image compression on the information fusion result. The compression selections are based on user needs, target type, and information fusion function, which is a subject of the operating conditions. Results are presented that modify the Video National Imagery Interpretability Ratio (VNIIRS) equations to include compression requirements for object recognition, fusion of results, and user selections. The target broker compression method would support image fusion system providing an exemplar of LLIF-HLIF interactions.
机译:信息融合由对象级评估的低级信息融合(LLIF)组成,该信息受传感器类型,环境条件和目标的许多操作条件的影响。同样,高级信息融合(HLIF)需要主动管理传感器参数。影响目标跟踪和识别的下游信息融合任务的参数的一个示例是上游图像压缩的参数。在本文中,我们提出了一种用于分析图像压缩对信息融合结果的影响的技术。压缩选择基于用户需求,目标类型和信息融合功能,而信息融合功能是操作条件的主题。提出的结果可以修改视频国家影像的可解释性比率(VNIIRS)公式,以包括对象识别,结果融合和用户选择的压缩要求。目标代理压缩方法将支持图像融合系统,提供LLIF-HLIF交互作用的范例。

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