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However, preserving thin retinal vessels during the filtering process is challenging due to vessels\u2019 small area and weak contrast compared to background, caused by the limited resolution of imaging and less blood flow in the vessel. In this paper, we present a novel retinal image denoising approach which is able to preserve the details of retinal vessels while effectively eliminating image noise. Specifically, our approach is carried out by determining an optimal spatial kernel for the bilateral filter, which is represented by a line spread function with an orientation and scale adjusted adaptively to the local vessel structure. Moreover, this approach can also be served as a preprocessing tool for improving the accuracy of the vessel detection technique. Experimental results show the superiority of our approach over state-of-the-art image denoising techniques such as the bilateral filter.<\/jats:p>","DOI":"10.1155\/2017\/1769834","type":"journal-article","created":{"date-parts":[[2017,2,5]],"date-time":"2017-02-05T16:01:06Z","timestamp":1486310466000},"page":"1-13","source":"Crossref","is-referenced-by-count":22,"title":["Retinal Image Denoising via Bilateral Filter with a Spatial Kernel of Optimally Oriented Line Spread Function"],"prefix":"10.1155","volume":"2017","author":[{"given":"Yunlong","family":"He","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5786-2491","authenticated-orcid":true,"given":"Yuanjie","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University, Jinan 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