COMPRESSIVE SENSING IN QUADRATURE FREQUENCY MODULATED THERMAL WAVE IMAGING

Abstract

Active thermography uses IR camera to capture the thermal response from a test sample to detect defects in the materials. Depending on the material geometry, externally Quadrature Frequency Modulated (QFM) optical stimulation consisting of very low frequency components usually less than 1 HZ is projected on the test sample. IR camera captures the thermal response from test material at a frequency much higher than the required nyquist rate. This is wastage of resources such as sensors, memory and power. In this paper Compressive Sensing (CS) is used to capture the thermal response from aluminum and bone test samples using IR camera at a reduced frame rate and then complete response is recovered using CS recovery algorithms Basis Pursuit (BP) and Orthogonal Matching Pursuit (OMP). Recovered thermal response is processed using correlation based pulse compression approach to perform subsurface analysis to detect the defects. To verify the effectiveness of the recovery algorithms comparison is done between original and recovered data and the results are promising.