Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

Hamidullah Binol; Abdullah Bal

doi:10.1117/12.2223917

17 May 2016 Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

Hamidullah Binol, Abdullah Bal

Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 98421G (2016) https://doi.org/10.1117/12.2223917
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That’s why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.

Citation Download Citation

Hamidullah Binol and Abdullah Bal "Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98421G (17 May 2016); https://doi.org/10.1117/12.2223917

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