{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T03:30:30Z","timestamp":1784172630195,"version":"3.55.0"},"reference-count":22,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,3]],"date-time":"2018-12-03T00:00:00Z","timestamp":1543795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In this paper, an edge detection method based on the regularized Laplacian operation is given. The Laplacian operation has been used extensively as a second-order edge detector due to its variable separability and rotation symmetry. Since the image data might contain some noises inevitably, regularization methods should be introduced to overcome the instability of Laplacian operation. By rewriting the Laplacian operation as an integral equation of the first kind, a regularization based on partial differential equation (PDE) can be used to compute the Laplacian operation approximately. We first propose a novel edge detection algorithm based on the regularized Laplacian operation. Considering the importance of the regularization parameter, an unsupervised choice strategy of the regularization parameter is introduced subsequently. Finally, the validity of the proposed edge detection algorithm is shown by some comparison experiments.<\/jats:p>","DOI":"10.3390\/sym10120697","type":"journal-article","created":{"date-parts":[[2018,12,3]],"date-time":"2018-12-03T06:02:09Z","timestamp":1543816929000},"page":"697","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Novel Edge Detection Method Based on the Regularized Laplacian Operation"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1628-3028","authenticated-orcid":false,"given":"Huilin","family":"Xu","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhui","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1109\/TSMCC.2002.804448","article-title":"Gaussian-based edge-detection methods\u2014A survey","volume":"32","author":"Basu","year":"2002","journal-title":"IEEE Trans. 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