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

J. Caulfield, J. Havlicek
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引用次数: 1

Abstract

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.
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使用多模式红外处理提取感兴趣区域的先进图像处理技术
随着大幅面单色和多色传感器的激增,对最终用户来说,在更大的数据量上查看和采取行动的挑战变得更具挑战性。我们报告了利用多处理模式有效提取目标的处理技术-焦平面阵列(FPA)传感器的多光谱带和多预处理数据带。我们已经开发了图像处理技术,解决了许多关键的预处理要求,包括静态和动态像素的基于场景的非均匀性校正,目标检测的多波段处理,以及在混乱的环境中减少和管理杂波和非目标。这些技术的主要动机包括图像预处理,提取具有潜在高可能性目标的图像集的小百分比,然后传输“活动”像素数据,同时忽略不变的像素。这些技术已经证明了原始数据的显著减少,并且允许最终用户更智能地为对象识别选择潜在的数据类型,而不需要人员参与。
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