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Detection of targets in terrain clutter by using multispectral infrared image processing

机译:利用多光谱红外图像处理检测地形杂波的目标

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A weighted-difference signal-processing algorithm for detecting ground targets by using dual- band IR data was investigated. Three variations of the algorithm were evaluated: (1) simple differences; (2) minimum noise; and (3) maximum SNR. The theoretical performance was compared to measured performance for two scenes collected by the NASA TIMS sensor over a rural area near Adelaide, Australia, and over a wooded area near the Redstone Arsenal. The theoretical and measured results agreed extremely well. For a given correlation coefficient and color ratio, the amount of signal-to-noise ratio gain can be predicted. However, target input SNRs and color ratios can vary considerably. For the targets and scenes evaluated here, the typical gains achieved ranged from a few dB loss (targets without color) to a maximum of approximately 20 dB.
机译:研究了一种通过使用双频带数据来检测地面目标的加权差分信号处理算法。评估算法的三种变化:(1)差异简单; (2)最小噪音; (3)最大SNR。将理论表现与NASA TIMS传感器在阿德莱德,澳大利亚附近的农村地区和Redstone Arsenal附近的树木繁茂的地区收集的两个场景进行了比较。理论和测量结果非常吻合。对于给定的相关系数和颜色比,可以预测信噪比增益的量。然而,目标输入SNR和颜色比率可以显着变化。对于此处评估的目标和场景,实现的典型增益从几个DB损耗(目标没有颜色的目标)范围为大约20dB。

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