Conventional methods for analysis of pulsed thermographic NDE sequence data are highly susceptible to noise, nonlinearity of the IR camera response, and the presence of surface features on the sample. Furthermore, the ability of conventional methods to significantly improve the ability to retrieve deep or weak subsurface features beyond the original unmodified image is limited. We have developed a Thermographic Signal Reconstruction (TSR) technique that enhances defect to background contrast, increases the depth range over which pulsed thermography can be applied, and reduces the amount of blurring due to lateral diffusion that is typical of thermographic imaging. The TSR approach also reduces the amount of data that must be stored by an order of magnitude. The reduction in size of the data structure allows simultaneous manipulation of data from numerous locations on a sample, so that fast parallel processing of large structure data is possible. The results of the parallel processed TSR data consistently offer higher spatial resolution, less blurring and more precise depth and size measurement than the original data.
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