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Proceedings Paper

Regression model for prediction of IR images
Author(s): Anuj Srivastava; Brian D. Thomasson; S. Richard F. Sims
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Paper Abstract

This paper develops a framework for predicting IR images of a target, in a partially observed thermal state, using known geometry and past IR images. The thermal states of the target are represented via scalar temperature fields. The prediction task becomes that of estimating the unobserved parts of the field, using the observed parts and the past patterns. The estimation is performed using regression models for relating the temperature variables, at different points on the target's surface, across different thermal states. A linear regression model is applied and some preliminary experimental results are presented using a laboratory target and a hand-held IR camera. Extensions to piecewise-linear and nonlinear models are proposed.

Paper Details

Date Published: 22 October 2001
PDF: 11 pages
Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445364
Show Author Affiliations
Anuj Srivastava, Florida State Univ. (United States)
Brian D. Thomasson, Florida State Univ. (United States)
S. Richard F. Sims, U.S. Army Aviation and Missile Command (United States)


Published in SPIE Proceedings Vol. 4379:
Automatic Target Recognition XI
Firooz A. Sadjadi, Editor(s)

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