标题:Nonlocal image denoising using edge-based similarity metric and adaptive parameter selection
作者:Fan Linwei;Li Xuemei;Guo Qiang;Zhang Caiming
作者机构:[Fan Linwei] School of Computer Science and Technology, Shandong University, Ji'nan, Shandong 250101, China.;[Li Xuemei] School of Computer Science an 更多
通讯作者:Zhang, Caiming(czhang@sdu.edu.cn)
通讯作者地址:[Zhang, CM]Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Shandong, Peoples R China;[Zhang, CM]Shandong Prov Key Lab Digital Media Technol, Jina 更多
来源:中国科学. 信息科学
出版年:2018
卷:61
期:4
DOI:10.1007/s11432-017-9207-9
摘要:We propose a nonlocal image denoising method with an edge-based similarity metric and adaptive parameter selection. The proposed denoising method uses a two-stage scheme to refine the denoising results. It first produces the central patch by the idea of nonlocal and then makes full use of the local structures to generate the central pixel. Consequently, the fine texture details can be effectively preserved using the proposed method.
收录类别:EI;CSCD;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040456571&doi=10.1007%2fs11432-017-9207-9&partnerID=40&md5=d16f88e65fb5ba05a8e30ecf60f82cfe
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