Image deconvolution techniques for motion blur compensation in DIC measurements
| Autor: | Emanuele Zappa, Alberto Lavatelli, Simone Turrisi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Digital image correlation
business.industry Motion blur Wiener filter ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology 01 natural sciences 010309 optics symbols.namesake 020303 mechanical engineering & transports 0203 mechanical engineering Robustness (computer science) 0103 physical sciences Cepstrum symbols Cepstral analysis Medicine Computer vision Artificial intelligence Deconvolution business Hardware_REGISTER-TRANSFER-LEVELIMPLEMENTATION Image restoration |
| Zdroj: | I2MTC |
| DOI: | 10.1109/i2mtc.2018.8409567 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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