We have located links that may give you full text access.
Reference-free metric for quantitative noise appraisal in holographic phase measurements.
This paper presents a reference-free metric for quantitative appraisal of de-noising algorithms for phase measurements in digital holography. In the literature, quality metrics are not self-contained because they require a noise-free reference phase fringe pattern in order to be computed. In practical situations, no exact phase is available to evaluate the quality of processing. In order to bypass such limitations, one needs a metric directly capable of providing information on how efficient the filtering is, without any help from any reference measurements and by only considering the measured available phase data. This paper presents a novel reference-free metric, called estimated phase error for quantitative appraisal of de-noising algorithms for noisy phase data processing. This metric is based on the computation of an estimator of the standard deviation of the phase error between data processed with an external algorithm and that from the evaluated algorithm. A benchmark, including 37 different de-noising algorithms, demonstrates that the proposed metric is capable of producing the same rankings as those obtained with classical metrics, requiring a reference phase. Application to phase data from mechanical testing demonstrates that the ranking obtained from experimental phase data is similar to that obtained during the benchmarking with simulated data.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app