基于Delaunay三角化的二维无约束优化EMD方法

doi:10.6040/j.issn.1672-3961.0.2018.245

Abstract

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

Jianping HU, Xin LI, Qi XIE, Ling LI, Daochang ZHANG. An unconstrained optimization EMD approach in 2D based on Delaunay triangulation[J].Journal of Shandong University(Engineering Science), 2018, 48(5): 9-15.

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References 22

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

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