Multichannel image denoising using color monogenic curvelet transform

DOI10.1007/s00500-016-2361-1zbMath1398.94032OpenAlexW2522248682MaRDI QIDQ1797753

Shan Gai

Publication date: 22 October 2018

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-016-2361-1

zbMATH Keywords

total variationcolor image denoisingcurvelet transformanalytic signalcolor monogenic wavelet transform

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• DT-CWT
• NSCT toolbox

Cites Work

• A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the Internet of things (IOT)
• Sparse directional image representations using the discrete shearlet transform
• The color monogenic signal: application to color edge detection and color optical flow
• Continuous curvelet transform. I: Resolution of the wavefront set
• Continuous curvelet transform. II: Discretization and frames
• Detecting Directionality in Random Fields Using the Monogenic Signal
• Total Nuclear Variation and Jacobian Extensions of Total Variation for Vector Fields
• Efficient Total Variation Minimization Methods for Color Image Restoration
• Steerable Wavelet Frames Based on the Riesz Transform
• The Discrete Shearlet Transform: A New Directional Transform and Compactly Supported Shearlet Frames
• Vector Extension of Monogenic Wavelets for Geometric Representation of Color Images
• Bayesian Learning of Sparse Multiscale Image Representations

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