22 October 2001 Regression model for prediction of IR images
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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.
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Anuj Srivastava, Anuj Srivastava, Brian D. Thomasson, Brian D. Thomasson, S. Richard F. Sims, S. Richard F. Sims, } "Regression model for prediction of IR images", Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445364; https://doi.org/10.1117/12.445364
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