Persistent hyperspectral adaptive multi-modal feature-aided tracking

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

doi:10.1117/12.818913

Translator Disclaimer

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

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

Author Affiliations +

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