Image Fusion for Enhancement of Defect Detectability of Al Metal Subsurface applying Lock-in Infrared Thermography

In this paper, the detectability for subsurface defects in aluminum specimen was analyzed using Lock-in thermography. The frequency applied were ranged from 0.01 to 0.1 Hz, The thermal image data acquired by the infrared thermographisc system were converted into phase and amplitude data through four-point Lock-in thermographic processing. Afterwards, image fusion was applied to improve the detection performance, and the signal-to-noise ratios for each frequency were calculated and compared. The results show that the detectability at each frequency was evaluated to achieve the enhanced detection for aluminum subsurface defects.