Covariance-based band selection and its application to near-real-time hyperspectral target detection

Jun-Hyung Kim; Jieun Kim; Yukyung Yang; Sohyun Kim; Hyun Sook Kim

doi:10.1117/1.OE.56.5.053101

9 May 2017 Covariance-based band selection and its application to near-real-time hyperspectral target detection

Jun-Hyung Kim, Jieun Kim, Yukyung Yang, Sohyun Kim, Hyun Sook Kim

Author Affiliations +

Optical Engineering, Vol. 56, Issue 5, 053101 (May 2017). https://doi.org/10.1117/1.OE.56.5.053101

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.

Citation Download Citation

Jun-Hyung Kim, Jieun Kim, Yukyung Yang, Sohyun Kim, and 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

Received: 1 December 2016; Accepted: 19 April 2017; Published: 9 May 2017

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available