Feature-preserving, mesh-free empirical mode decomposition for point clouds and its applications

DOI10.1016/j.cagd.2017.11.002zbMath1381.65021OpenAlexW2773895715MaRDI QIDQ1693667

Dongbo Zhang, Xiaochao Wang, Hong Qin, Lixin Guo, Aimin Hao, Jian-Ping Hu

Publication date: 31 January 2018

Published in: Computer Aided Geometric Design (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cagd.2017.11.002

zbMATH Keywords

algorithmnumerical exampleempirical mode decompositioneigenvalue decompositionpoint cloudsmulti-scale decompositionfeature-preserving analysis and processingnonlinear signalstructure measurementtime series processing

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Unnamed Item
• Wavelets on graphs via spectral graph theory
• Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures
• Iterations of a non-linear transformation for enhancement of digital images
• Novel and efficient computation of Hilbert-Huang transform on surfaces
• A confidence limit for the empirical mode decomposition and Hilbert spectral analysis
• Feature-Oriented Image Enhancement Using Shock Filters
• Two-dimensional empirical mode decomposition by finite elements
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
• Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding
• Edge-aware point set resampling
• Partial Differential Equation-Based Approach for Empirical Mode Decomposition: Application on Image Analysis

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