Bidimensional empirical mode decomposition-based diffusion filtering for image denoising

DOI10.1007/s00034-020-01404-yzbMath1485.94007OpenAlexW3014014783MaRDI QIDQ831572

Himanshu Singh, Varun Bajaj, Sethu Venkata Raghavendra Kommuri, Anil Kumar

Publication date: 23 March 2022

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-020-01404-y

zbMATH Keywords

image denoisingintrinsic mode functionbidimensional empirical mode decompositiondiffusion filtergradient threshold

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Nonlinear total variation based noise removal algorithms
• Anisotropic diffusion with generalized diffusion coefficient function for defect detection in low-contrast surface images
• Selection of optimal stopping time for nonlinear diffusion filtering
• Iterative Parameter-Choice and Multigrid Methods for Anisotropic Diffusion Denoising
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

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