标题:Image Smoothing Based on Image Decomposition and Sparse High Frequency Gradient
作者:Ma Guanghao;Zhang Mingli;Li Xuemei;Zhang Caiming
通讯作者:Li, Xue-Mei(xmli@sdu.edu.cn)
作者机构:[Ma Guanghao] School of Computer Science and Technology, Shandong University, Jinan, Shandong 250101, China.;[Zhang Mingli] Shandong Co-Innovation Cen 更多
会议名称:6th International Conference on Computational Visual Media (CVM)
会议日期:APR 18-20, 2018
来源:计算机科学技术学报
出版年:2018
卷:33
期:3
页码:502-510
DOI:10.1007/s11390-018-1834-3
关键词:image smoothing; texture removal; image decomposition
摘要:Image smoothing is a crucial image processing topic and has wide applications. For images with rich texture, most of the existing image smoothing methods are difficult to obtain significant texture removal performance because texture containing obvious edges and large gradient changes is easy to be preserved as the main edges. In this paper, we propose a novel framework (DSHFG) for image smoothing combined with the constraint of sparse high frequency gradient for texture images. First, we decompose the image into two components: a smooth component (constant component) and a non-smooth (high frequency) component. Second, we remove the non-smooth component containing high frequency gradient and smooth the other component combining with the constraint of sparse high frequency gradient. Experimental results demonstrate the proposed method is more competitive on efficiently texture removing than the state-of-the-art methods. What is more, our approach has a variety of applications including edge detection, detail magnification, image abstraction, and image composition.
收录类别:CPCI-S;EI;CSCD;SCOPUS;SCIE
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046873725&doi=10.1007%2fs11390-018-1834-3&partnerID=40&md5=aba792e567fe3feaaf98b9659864d593
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