Thermal Saliency-Based Spatial Weighting With Nonlinear Enhancement for Principal Component Thermography in ECPT

The detection of weak defects in eddy current pulsed thermography is hampered by nonuniform heating and thermal diffusion, which cause low signal-to-noise ratio (SNR). While conventional principal component thermography (PCT) is widely used for data reduction, its nature as a “blind” statistical tool often fails to separate these subtle defect signatures from the dominant background noise. To address this, we adapt conventional PCT by introducing a saliency-based spatial weighting strategy. The core innovation is a weighting scheme where a spatial saliency map, derived from time-integrated thermal energy, is nonlinearly enhanced via a gamma transformation. Integrating this high-contrast weight map into the PCT algorithm transforms it from a blind statistical tool into a targeted, guided analysis. Validated on six diverse metallic specimens, the proposed spatially weighted PCT (SW-PCT) significantly outperforms traditional PCT and other representative methods in SNR, especially for enhancing weak defects. An optimized vectorized implementation ensures high computational efficiency, establishing SW-PCT as a robust solution that balances detection accuracy and processing speed for industrial nondestructive testing applications.