Anomalies detected in hyperspectral images using the RX-based detector

Jee-Cheng Wu; Geng-Gui Wang

doi:10.1117/12.2324879

9 October 2018 Anomalies detected in hyperspectral images using the RX-based detector

Jee-Cheng Wu, Geng-Gui Wang

Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 107891B (2018) https://doi.org/10.1117/12.2324879
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

The anomaly detector (AD) is an important topic in the exploitation of hyperspectral image (HSI). Because unsupervised AD can detect the objects whose spectra are different from their surroundings under the conditions of no spectral libraries and atmospheric correction, it becomes increasingly important in hyperspectral military and civilian applications. Although there have been many ADs proposed, the Reed-Xialoi detector (RXD) is the most typical one, which has been successfully applied to many practical applications in terms of HSI anomaly detection. However, RXD suffers from “small sample size” problem. This paper focuses on the investigation of the three issues related to anomaly detection in real HSIs. That is, how many pixels of a target will be detected as an anomaly? Then, is an anomaly responded to its proximity? Finally, what kinds of anomalies will be detected? Some well-known RX-based detectors are programmed, such as global RX, local RX, subspace RX, weight Rx and uniform target detector. And those detectors are applied to three hyperspectral datasets acquired by both the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperspectral Digital Imagery Collection Experiment (HYDICE) sensors. Experimental results show that an anomaly pixel is detected, if at least one similar pixel is found at 8-surrounding pixels. The detected anomaly pixels respond to the selected background rather than to spatial neighborhood relationship. Moreover, the RX-based detectors can’t recognize detected anomaly attributes, and no one RX-based detector performance is statistically superior to the others.

Citation Download Citation

Jee-Cheng Wu and Geng-Gui Wang "Anomalies detected in hyperspectral images using the RX-based detector", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 107891B (9 October 2018); https://doi.org/10.1117/12.2324879

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Sensors

Hyperspectral imaging

Target detection

Hyperspectral target detection

Advanced distributed simulations

Detection and tracking algorithms

Data acquisition

Show All Keywords

Keywords/Phrases

Search In:

Publication Years