A Simultaneous Cartoon-Texture Image Segmentation and Image Decomposition Method

被引:5
作者
Li Yafeng [1 ]
Zhao Qijun [2 ,3 ]
Zhang Wenbo [1 ]
Fan Pan [1 ]
Zhang Renrui [4 ]
Sun Jieqi [1 ]
Li Jing [1 ]
机构
[1] Baoji Univ Arts & Sci, Sch Comp Sci & Technol, Baoji 721016, Peoples R China
[2] Sichuan Univ, Coll Comp Sci, Chengdu 610065, Peoples R China
[3] Tibet Univ, Sch Informat Sci & Technol, Lhasa 850000, Peoples R China
[4] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
Image segmentation; Image decomposition; Variational model; Dictionary learning; TOTAL VARIATION MINIMIZATION;
D O I
10.1049/cje.2020.08.006
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Image segmentation and image decomposition are fundamental problems in image processing. Image decomposition methods for separating images into cartoon and texture components can effectively serve different image processing tasks because different components can be respectively treated in more effective way. However, image decomposition methods are currently simply taken as an independent preprocessing step, and particularly in image segmentation different effects of cartoon and texture components have not been considered. This paper presents a novel simultaneous cartoon-texture image segmentation and image decomposition method to boost the performance of both segmentation and decomposition. We design a fast alternating optimization algorithm to solve the proposed model. Experimental results demonstrate the outstanding performance of the proposed method on both image segmentation and image decomposition.
引用
收藏
页码:906 / 915
页数:10
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