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

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Abstract
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.

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