Ms. Devorah N. Rotman Profile

Devorah N. Rotman

at Ben-Gurion Univ. of the Negev

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Proceedings Article | 31 May 2022 Presentation + Paper

Comparison between the additive and substitutive models

T. Shapira, D. Rotman, S. Rotman

Proceedings Volume 12094, 120940O (2022) https://doi.org/10.1117/12.2605968

KEYWORDS: Target detection, Detection and tracking algorithms, Hyperspectral target detection, Data modeling, Hyperspectral imaging, Image segmentation, Error analysis, Algorithms

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Several different algorithms have been suggested for matched target detection for solid and gas point targets: theoretically, gas targets lead to an additive point target detection algorithm while solid targets lead to a substitutive point target detection algorithm. In this paper, we consider deviations that may occur in real life non-stationary backgrounds that would complicate the choice of algorithm. In particular, we have identified three possible weaknesses to the substitutive algorithm. First, incorrect estimates of the background for a minority of pixels can lead to considerably worse results in the substitutive algorithm compared to the additive algorithm. Second, an accurate knowledge of the amplitude (or power) of the target is needed for the substitutive algorithm compared to the additive algorithm. Thirdly, due to adjacency effects, it is not obvious which model to use in certain cases. For this latter case, we consider a hybrid model originally proposed by A. Ziemann et al. [1]. This model, with an adaptive parameter estimate of the form of the detection to use, appears to be a reasonable substitute for the two aforementioned algorithms.

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