{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T14:34:13Z","timestamp":1775486053008,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51976159"],"award-info":[{"award-number":["51976159"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In particle image velocimetry (PIV) experiments, background noise inevitably exists in the particle images when a particle image is being captured or transmitted, which blurs the particle image, reduces the information entropy of the image, and finally makes the obtained flow field inaccurate. Taking a low-quality original particle image as the research object in this research, a frequency domain processing method based on wavelet decomposition and reconstruction was applied to perform particle image pre-processing. Information entropy analysis was used to evaluate the effect of image processing. The results showed that useful high-frequency particle information representing particle image details in the original particle image was effectively extracted and enhanced, and the image background noise was significantly weakened. Then, information entropy analysis of the image revealed that compared with the unprocessed original particle image, the reconstructed particle image contained more effective details of the particles with higher information entropy. Based on reconstructed particle images, a more accurate flow field can be obtained within a lower error range.<\/jats:p>","DOI":"10.3390\/e26070573","type":"journal-article","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T11:33:53Z","timestamp":1719920033000},"page":"573","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Information Entropy Analysis of a PIV Image Based on Wavelet Decomposition and Reconstruction"],"prefix":"10.3390","volume":"26","author":[{"given":"Zhiwu","family":"Ke","sequence":"first","affiliation":[{"name":"Science and Technology on Thermal Energy and Power Laboratory, Wuhan Second Ship Design and Research Institute, Wuhan 430025, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0555-2771","authenticated-orcid":false,"given":"Wei","family":"Zheng","sequence":"additional","affiliation":[{"name":"Science and Technology on Thermal Energy and Power Laboratory, Wuhan Second Ship Design and Research Institute, Wuhan 430025, China"}]},{"given":"Xiaoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Energy and Power Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8934-3450","authenticated-orcid":false,"given":"Mei","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Energy and Power Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/s00348-019-2792-4","article-title":"High-speed tomographic PIV measurements in a DISI engine","volume":"60","author":"Braun","year":"2019","journal-title":"Exp. 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