Reconstruction and enhancement of active thermographic image sequences

Abstract

Active thermography has gained broad acceptance as a nondestructive evaluation method for numerous in-service and manufacturing applications in the aerospace industry. However, because of the diffusive nature of the process, it is subject to blurring and degradation of the signal as one attempts to image deeper subsurface features. Despite this constraint, active thermographic response is deterministic, to the extent that the postexcitation time evolution for a defect-free sample can be accurately predicted using a simple one-dimensional model. In the patented thermal signal reconstruction method, the time history of every pixel in the field of view is compared to such a model in the logarithmic domain, where deviations from ideal behavior are readily identifiable. The process separates temporal and spatial nonuniformity noise components in the image sequence and significantly reduces temporal noise. Time-derivative images derived from the reconstructed data allow detection of subsurface defects at earlier times in the sequence than conventional contrast images, significantly reducing undesirable blurring effects and facilitating detection of low-thermal-contrast features that may not be detectable in the original data sequence.