Persistent hyperspectral adaptive multi-modal feature-aided tracking

Andrew C. Rice; Juan R. Vasquez; John Kerekes; Michael J. Mendenhall

doi:10.1117/12.818913

27 April 2009 Persistent hyperspectral adaptive multi-modal feature-aided tracking

Andrew C. Rice, Juan R. Vasquez, John Kerekes, Michael J. Mendenhall

Proceedings Volume 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV; 73340M (2009) https://doi.org/10.1117/12.818913
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

An architecture and implementation is presented regarding persistent, hyperspectral, adaptive, multi-modal, feature-aided tracking within the urban context. A novel remote-sensing imager has been designed which employs a micro-mirror array at the focal plane for per-pixel adaptation. A suite of end-to-end synthetic experiments have been conducted, which include high-fidelity moving-target urban vignettes, DIRSIG hyperspectral rendering, and full image-chain treatment of the prototype adaptive sensor. Corresponding algorithm development has focused on: motion segmentation, spectral feature modeling, classification, fused kinematic/spectral association, and adaptive sensor feedback/control.

Citation Download Citation

Andrew C. Rice, Juan R. Vasquez, John Kerekes, and Michael J. Mendenhall "Persistent hyperspectral adaptive multi-modal feature-aided tracking", Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73340M (27 April 2009); https://doi.org/10.1117/12.818913

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