value is stored in the table to provide training data for the neural network measurements are made on materials of known thermal properties in the simplest version a set of calibrants is taken with surface topography that varies from the very smooth to the very rough the approach that is illustrated in the fig5 and the table in fig5 a relies on using in the training set the height differences between the pixel and its adjacent u201c nearest neighbor u201d pixels in general pixels further removed from the pixel could be included and it would generally be preferable to do this although in that case more time would be required to train a system using a neural network for all of these samples the u201c true u201d thermal measurement is the value obtained on the very smooth surface and stored in the table for a completely smooth compositionally homogeneous sample the same thermal response should be measured at each point on the sample 39 s surface in practice an average value from the smoothest available surface of the sample can sometimes be taken as the u201c true u201d value when a suitable set of calibrants is not available or insufficient time is available for calibration.