Environmentally-adaptive target recognition for SAS imagery

Xiaoxiao Du; Anand Seethepalli; Hao Sun; Alina Zare; J. Tory Cobb

doi:10.1117/12.2262688

3 May 2017 Environmentally-adaptive target recognition for SAS imagery

Xiaoxiao Du, Anand Seethepalli, Hao Sun, Alina Zare, J. Tory Cobb

Proceedings Volume 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII; 101820I (2017) https://doi.org/10.1117/12.2262688
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Characteristics of underwater targets displayed in synthetic aperture sonar (SAS) imagery vary depending on their environmental context. Discriminative features in sea grass may differ from the features that are discriminative in sand ripple, for example. Environmentally-adaptive target detection and classification systems that take into account environmental context, therefore, have the potential for improved results. This paper presents an end-to-end environmentally-adaptive target detection system for SAS imagery that performs target recognition while accounting for environmental context. First, locations of interest are identified in the imagery using the Reed-Xiaoli (RX) detector and a Non-Gaussian detector based on the multivariate Laplace distribution. Then, the Multiple Instance Learning via Embedded Instance Selection (MILES) approach is used to identify the environmental context of the targets. Finally, target features are extracted and a set of environmentally-specific k-Nearest Neighbors (k-NN) classifiers are applied. Experiments were conducted on a collection of both high and low frequency SAS imagery with a variety of environmental contexts and results show improved classification accuracy between target classes when compared with classification results with no environmental consideration.

Conference Presentation

Citation Download Citation

Xiaoxiao Du, Anand Seethepalli, Hao Sun, Alina Zare, and J. Tory Cobb "Environmentally-adaptive target recognition for SAS imagery", Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, 101820I (3 May 2017); https://doi.org/10.1117/12.2262688

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