9 May 2017 Covariance-based band selection and its application to near-real-time hyperspectral target detection
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Abstract
The matched filter (MF) and adaptive coherence estimator (ACE) show great effectiveness in hyperspectral target detection applications. Practical applications in which on-board processing is generally required demand real-time or near-real-time implementation of these detectors. However, a vast amount of hyperspectral data may make real-time or near-real-time implementation of the detection algorithms almost impossible. Band selection can be one of the solutions to this problem by reducing the number of spectral bands. We propose a new band selection method that prioritizes spectral bands based on their influence on the detection performance of the MF and ACE and discards the least influential bands. We validate the performance of our method using real hyperspectral images. We also demonstrate our technique on near-real-time detection tasks and show it to be a feasible approach to the tasks.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Jun-Hyung Kim, Jun-Hyung Kim, Jieun Kim, Jieun Kim, Yukyung Yang, Yukyung Yang, Sohyun Kim, Sohyun Kim, Hyun Sook Kim, Hyun Sook Kim, } "Covariance-based band selection and its application to near-real-time hyperspectral target detection," Optical Engineering 56(5), 053101 (9 May 2017). https://doi.org/10.1117/1.OE.56.5.053101 . Submission: Received: 1 December 2016; Accepted: 19 April 2017
Received: 1 December 2016; Accepted: 19 April 2017; Published: 9 May 2017
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