Ray-tracing approach for realistic hyperspectral forest canopies

J. Russ Moulton Jr.; Christopher E. Fink

doi:10.1117/12.478828

6 August 2002 Ray-tracing approach for realistic hyperspectral forest canopies

J. Russ Moulton Jr., Christopher E. Fink

Proceedings Volume 4718, Targets and Backgrounds VIII: Characterization and Representation; (2002) https://doi.org/10.1117/12.478828
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

A compelling figure-of-merit for synthetic sensor data generation is target acquisition performance relative to field data of similar scenarios. That is, if one synthesized a sensor data set from the ground truth of an actual field measurement, one would expect a realistic simulation to give rise to probabilities of target detection and identification, and false alarm rates comparable to that of the field data. This correlation would, of course, be expected to extend to both human and machine-based performance. Key to this correlation is realistic background synthesis, providing appropriate spatial and spectral competition with the target signatures for both man and algorithm. Hyperspectral target signature synthesis is fairly mature, while background modeling for target- competitive clutter leaves much to be desired. The authors herein detail a ray-tracing approach for rigorous hyperspectral background signature synthesis that focuses on trees and forest canopies, and synthesis techniques for producing spatial-spectral statistics consistent with field data. In addition, the authors present some of the hyperspectral synthesis components, including the signature model, which can be used in a multi-spectral mode for real- time EO/IR image synthesis.

Citation Download Citation

J. Russ Moulton Jr. and Christopher E. Fink "Ray-tracing approach for realistic hyperspectral forest canopies", Proc. SPIE 4718, Targets and Backgrounds VIII: Characterization and Representation, (6 August 2002); https://doi.org/10.1117/12.478828

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