{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:10:40Z","timestamp":1760235040083,"version":"build-2065373602"},"reference-count":77,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The imperfections of image acquisition systems produce noise. The majority of edge detectors, including gradient-based edge detectors, are sensitive to noise. To reduce this sensitivity, the first step of some edge detectors\u2019 algorithms, such as the Canny\u2019s edge detector, is the filtering of acquired images with a Gaussian filter. We show experimentally that this filtering is not sufficient in case of strong Additive White Gaussian or multiplicative speckle noise, because the remaining grains of noise produce false edges. The aim of this paper is to improve edge detection robustness against Gaussian and speckle noise by preceding the Canny\u2019s edge detector with a new type of denoising system. We propose a two-stage denoising system acting in the Hyperanalytic Wavelet Transform Domain. The results obtained in applying the proposed edge detection method outperform state-of-the-art edge detection results from the literature.<\/jats:p>","DOI":"10.3390\/rs13152888","type":"journal-article","created":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T10:31:44Z","timestamp":1627036304000},"page":"2888","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Hyperanalytic Wavelet-Based Robust Edge Detection"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0510-7344","authenticated-orcid":false,"given":"Alexandru","family":"Isar","sequence":"first","affiliation":[{"name":"Communications Department, Politehnica University, 300223 Timisoara, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0227-1061","authenticated-orcid":false,"given":"Corina","family":"Nafornita","sequence":"additional","affiliation":[{"name":"Communications Department, Politehnica University, 300223 Timisoara, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6952-5321","authenticated-orcid":false,"given":"Georgiana","family":"Magu","sequence":"additional","affiliation":[{"name":"Communications Department, Politehnica University, 300223 Timisoara, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"919","DOI":"10.13164\/re.2018.0919","article-title":"About Edge Detection in Digital Images","volume":"27","author":"Hagara","year":"2018","journal-title":"Radioengineering"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A Computational Approach to Edge Detection","volume":"6","author":"Canny","year":"1986","journal-title":"IEEE Trans. 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