2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)(2022)
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摘要
A Bayesian Likelihood Ratio Test (LRT) detector is analytically derived here for the replacement target model and using the non-parametric variable-bandwidth kernel density estimator to model the hyperspectral background. The detector is compared to the recent Generalized LRT detector, based on the same non-parametric model for the background. Experimental results obtained on two hyperspectral sub-pixel target detection scenarios reveal the great potential of the proposed detector and set the basis for future investigations.
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关键词
Hyperspectral,Target Detection,Bayes,non-parametric,replacement model