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Evaluation of De-Noising Algorithms for Phase Data Filtering in Digital Holographic Metrology

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Abstract

This paper presents a comparison between multiple image denoising algorithms in the context of speckle noise in phase data from digital holography. Several denoising algorithms are tested on simulated noisy speckled phase and images. The paper shows that curvelets demonstrated most efficiency, in terms both of gain in the SNR ratio and of phase error. This approach surpasses the algorithms used for the SAR images, which, however, use the same noise model as inherent to the phase fringe patterns.

© 2015 Optical Society of America

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