Journal of Shandong University(Engineering Science) ›› 2018, Vol. 48 ›› Issue (5): 9-15.doi: 10.6040/j.issn.1672-3961.0.2018.245

• Machine Learning & Data Mining • Previous Articles     Next Articles

An unconstrained optimization EMD approach in 2D based on Delaunay triangulation

Jianping HU1,2(),Xin LI1,Qi XIE1,3,*(),Ling LI1,Daochang ZHANG1   

  1. 1. College of Science, Northeast Electric Power University, Jilin 132012, Jilin, China
    2. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
    3. School of Mathematical Science, Jilin University, Changchun 130012, Jilin, China
  • Received:2018-06-07 Online:2018-10-20 Published:2018-06-07
  • Contact: Qi XIE E-mail:neduhjp307@163.com;xieqi_19820302@126.com
  • Supported by:
    国家自然科学基金资助项目(61672149);吉林省科技发展计划基金资助项目(20170520052JH);吉林省教育厅十三五科学技术研究基金资助项目(吉教科合字[2016]第97号);北京航空航天大学虚拟现实技术与系统国家重点实验室开放基金资助项目(BUAA-VR-16KF-23)

Abstract:

An improved unconstrained optimization empirical mode decomposition (EMD) approach in two-dimensional (2D) based on Delaunay triangulation was presented. It firstly redefined the extremum of 2D images, and then constructed an optimization model to decompose the input image iteratively based on the Delaunay triangulation of the image extrema. The proposed approach could adaptively decompose the input image into several intrinsic mode images with fine-coarse scales and a residue. Experiment results demonstrated the proposed method had more powerful capabilities in capturing the multi-scale details and image features than the original 2D unconstrained optimization EMD approach.

Key words: empirical mode decomposition, unconstrained optimization, Delaunay triangulation, intrinsic mode image, multi-scale feature

CLC Number: 

  • TP391

Fig.1

Comparison of constraint point selection methods"

Fig.2

Decomposition comparison of different extremum parameter selection methods"

Fig.3

Decomposition comparison between the method used the nearest point modeling (the first row) and the method used Delaunay triangulation (the second row) in this research"

Fig.4

Decomposition comparison for a manmade image"

Fig.5

Decomposition comparison of the Woman image"

Fig.6

Decomposition comparison of the MRI image"

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