Image deconvolution techniques for motion blur compensation in DIC measurements

Digital image correlation (DIC) measurements are affected by several sources of uncertainty. Motion blur is one of the most relevant problems in dynamic DIC applications. This work deals with the problem of compensating motion blur effects on DIC. Firstly, a robust motion blur estimation technique based on cepstral analysis is presented and validated. Secondly, the problem of image restoration has been tackled. Two image deconvolution techniques are presented: one based on cepstrum deconvolution and the other based on Wiener filter. The latter has shown better robustness in presence of noise. Each presented technique has been tested with synthetic DIC experiments. Results demonstrate that both the compensation algorithms are able to improve the accuracy of DIC measurement in presence of motion blur.