Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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In particle image velocimetry (PIV), the brightness of a particle image sequence may change due to uneven laser intensity distribution and fluctuations in laser output. Consequently, the optical flow method (OFM), which relies on the brightness constancy assumption, becomes unsuitable. The traditional variational OFM is only accurate for small displacement fields but lacks robustness and accuracy when applied to PIV images with intensity variations. In this study, to address these issues, we improve the traditional cross-correlation OFM to establish a high-resolution hybrid cross-correlation optical flow method (CC-OFM) for particle images with large displacement and intensity variations. The data term, which combines the brightness constancy assumption with the gradient constancy assumption, compensates for the intensity changes between the particle image pairs. The proposed CC-OFM is quantitatively evaluated using both synthetic particle images and experimental particle images under various conditions, comparing the displacement results with those obtained using other methods. The results reveal that the proposed CC-OFM provides high accuracy and robustness for particle images with large displacement and intensity variations. Furthermore, its high spatial resolution allows it to capture flow details more effectively than the other methods.
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http://dx.doi.org/10.1063/5.0238355 | DOI Listing |