Thermal wave imaging for defect detection is a relatively new concept. However, the technique is accepted widely, due to its fast testing speed, low cost. The present paper deals with the data processing part of images obtained from the lock-in experiments for defect detection. The SNR calculation forms an important part of lock-in experiments for quantitative study of defects at different depth. The results of SNR are based on the way a signal is defined. The algorithm followed for SNR calculation, thus is important. An algorithm for SNR calculation for defect quantification in lock-in thermal wave imaging is described here.
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Roy et al. (2016) studied this question.
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