title: Retinal Image Denoising via Bilateral Filter with a Spatial Kernel of Optimally Oriented Line Spread Function.
abstract: Filtering belongs to the most fundamental operations of retinal image processing and for which the value of the filtered image at a given location is a function of the values in a local window centered at this location. However, preserving thin retinal vessels during the filtering process is challenging due to vessels' 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.
authors.affiliation: School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China.
authors.forename: Yunlong
authors.initials: Y
authors.lastname: He
authors.affiliation: School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute of Life Sciences, Shandong Normal University, Jinan 250014, China; Key Laboratory of Intelligent Information Processing, Shandong Normal University, Jinan 250014, China.
authors.forename: Yuanjie
authors.identifier: 0000-0002-5786-2491
authors.initials: Y
authors.lastname: Zheng
authors.affiliation: School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China.
authors.forename: Yanna
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: School of Psychology, Shandong Normal University, Jinan 250014, China.
authors.forename: Yanju
authors.initials: Y
authors.lastname: Ren
authors.affiliation: School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China.
authors.forename: Jian
authors.identifier: 0000-0003-0305-8454
authors.initials: J
authors.lastname: Lian
authors.affiliation: Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: James
authors.initials: J
authors.lastname: Gee
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D016477:Artifacts; D004058:Diffusion; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D015233:Models, Statistical; D016011:Normal Distribution; D012160:Retina / Q000033:anatomy & histology*; D012171:Retinal Vessels / Q000033:anatomy & histology*