Abstract
The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern. This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown. The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects.
How to Cite:
Ahmadi, S. ., Thiel, E. ., Karagianni, C. ., Hirsch, P. ., Ziegler, M. ., Burgholzer, P. ., Mayr, G. ., Jung, P. . & Caire, G. ., (2019) “Photothermal super resolution image reconstruction using structured 1D laser illumination”, Review of Progress in Quantitative Nondestructive Evaluation .
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