A Hierarchical Framework on Affinity Based Image Matting

被引：0
|
作者：
Yao G.-L. [1 ,2 ]
Zhao Z.-J. [1 ,2 ]
Su X.-D. [1 ,2 ]
Xin H.-T. [1 ,2 ]
Hu W. [1 ,2 ]
Qin X.-L. [1 ]
机构：
[1] School of Computer and Information Engineering, Harbin University of Commerce, Harbin
[2] Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2021年 / 47卷 / 01期
关键词：
Affinity based matting; Color line model; Image matting; KNN (K-nearest neighbor) searching; Matting Laplacian;
D O I：
10.16383/j.aas.c180356
中图分类号：
学科分类号：
摘要：
Affinity based image matting methods can be categorized into KNN (K-nearest neighbor) based matting and matting Laplacian based matting, and this paper raises a hierarchical framework on affinity based matting according to the analyses of the advantages of these two popular affinity based image matting methods. The first opaque pixel classification layer, also named as pre-processing layer, employs a relatively far searching fashion based on simple weights in KNN and is spatial irrelevant to the unknown region of the initial Trimap. The second mixed pixel computation layer, also named as final matting layer, adaptively adjusts the kernel size of the color line model in matting Laplacian according to the remaining size of the unknown region. Each layer adjusts proper searching range adaptively according to the overlapping degree between global foreground and background colors. The following distinctions are provided in the experiments. First, several representative matting algorithms are processed after the first layer to show the superiority and compatibility of our pre-processing method over other pre-processing methods. Second, several alternative matting methods are also processed after the first layer to show the superiority of our final matting method over other matting methods. Experimental results show that our approach can greatly raise the solving precisions for both opaque and mixed pixels. Copyright © 2021 Acta Automatica Sinica. All rights reserved.
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页码：209 / 223
页数：14
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