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Advanced image processing techniques for extracting regions of interest using multimode IR processing

机译:用于使用多模IR处理提取感兴趣区域的高级图像处理技术

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As large format single color and multicolor sensors proliferate challenges in viewing and taking action on a much higher data volume becomes challenging to end users. We report on processing techniques to effectively extract targets utilizing multiple processing modes — both multiple spectral band and multiple pre-processed data bands from Focal Plane Array (FPA) sensors. We have developed image processing techniques which address many of the key pre-processing requirements, including scene based non-uniformity correction of static and dynamic pixels, multiband processing for object detection, and reduction and management of clutter and non-targets in a cluttered environment. Key motivations for these techniques include image pre-processing extracting small percentages of the image set with potentially high likelihood targets and then transmitting “active” pixel data while ignoring unchanging pixels. These techniques have demonstrated significant reductions in the raw data, and allow the end user to more intelligently select potential data types for object identification without requiring a person in the loop.
机译:随着大型格式的单色和多色传感器在观看和采取行动方面激增了更高的数据量的挑战变得挑战到最终用户。我们报告了利用多个处理模式有效提取目标的处理技术 - 来自焦平面阵列(FPA)传感器的多频带和多个预处理数据带。我们开发了图像处理技术,该技术解决了许多关键的预处理要求,包括基于静态和动态像素的场景的非均匀性校正,对象检测的多频带处理,以及杂乱环境中的杂波和非目标的减少和管理。这些技术的关键动机包括提取具有潜在高似然目标的图像集的小百分比,然后在忽略不变像素的同时发送“活动”像素数据。这些技术已经证明了原始数据中的显着减少,并且允许最终用户更智能地选择对象识别的潜在数据类型而不需要循环中的人。

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