An information theoretic model of target discrimination using hyperspectral and multisensor data

Niclas Wadströmer; Ingmar Renhorn

doi:10.1117/12.780192

Abstract

We address the problem of target discrimination using hyperspektral and multisensor data. The problem is of significance to detection and classification of low signature targets such as landmines. The problem will be described with stochastic models and by using information theoretic concepts we will derive limits to system performance in terms of probability of false alarm and probablility of detection. The stochastic model is suitable to evaluate and optimize sensor parameters and sensor configurations. We will for example investigate how much information different combinations of spectral and spatial data will give. With the stochastic model sensors with different types of characteristics can be compared and the contribution of the different sensors and configurations can be evaluated. Besides the optimization of different sensor configurations with respect to specific applications, the stochastic model will be used to evaluate different anomaly detectors. The strength of our approach is shown by examples from an analysis of measurements on a natural scene with various objects using an electro-optical hyperspectral sensor and several other sensors. We expect that our approach will give significant indications on how to choose and configure sensors for efficient and reliable target discrimination.

Citation Download Citation

Niclas Wadströmer, Niclas Wadströmer, Ingmar Renhorn, Ingmar Renhorn, } "An information theoretic model of target discrimination using hyperspectral and multisensor data", Proc. SPIE 6940, Infrared Technology and Applications XXXIV, 69402H (18 April 2008); doi: 10.1117/12.780192; https://doi.org/10.1117/12.780192

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