Target detection in hyperspectral images using basic thresholding classifier

2017-05-18
TOKSÖZ, Mehmet Altan
Ulusoy, İlkay
In this letter, we propose target detector version of recently introduced basic thresholding classifier for hyperspectral images. The proposed technique is a sparsity-based low complexity detector which achieves high detection rates with very low false alarm rates and performs extremely rapidly. We also propose a new decision metric, background model, and spatial smoothing procedure in order to increase the detection probability further. Experiments show that the presented method outperforms the other state-of-the-art sparsity-based approaches.
Citation Formats
M. A. TOKSÖZ and İ. Ulusoy, “Target detection in hyperspectral images using basic thresholding classifier,” 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37944.