This paper illustrates an image processing technique using the Proper Orthogonal Decomposition (POD) of infrared thermal data for the construction of reduced models starting from experimental data. We consider a thin steel plate with a point heat source in the middle activated at time=0. A TELOPS DSP-83 fast IR camera collects a sequence of infrared image data. The 2D samples constitute the data set used to generate a POD empirical basis. Galërkin projection of the heat conduction PDE onto the basis generates the finite dimensional approximate dynamical system. Results are compared with experimental data and analytical solution.

This presentation is part of Minisymposium “MS53 - Dimensionality Reduction Algorithms for Large-Scale Images (2 parts)”
organized by: Salvatore Cuomo (Dept. Mathematics and Applications "Renato Caccioppoli", University of Naples) , Costantinos Siettos (National Technical University of Athens ) , Lucia Russo (Consiglio Nazionale delle Ricerche, Istituto di Ricerche sulla Combustione) .

Authors:

Lucia Russo (Consiglio Nazionale delle Ricerche, Istituto di Ricerche sulla Combustione)

Gaetano Continillo (University of Sannio, Benevento)

Keywords:

image reconstruction, partial differential equation models