Speckle Reduction via Higher Order Total Variation Approach

DOI10.1109/TIP.2014.2308432zbMath1374.94110WikidataQ51089191 ScholiaQ51089191MaRDI QIDQ4592161

Yang Gao, Wensen Feng, Hong Lei

Publication date: 20 November 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Mathematics Subject Classification ID

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

Related Items (12)

Speckle noise removal in ultrasound images by first- and second-order total variation ⋮ Fractional 1-Laplacian evolution equations to remove multiplicative noise ⋮ Speckle noise reduction via nonconvex high total variation approach ⋮ An adaptive total generalized variational model for speckle reduction in ultrasound images ⋮ Speckle reduction with trained nonlinear diffusion filtering ⋮ Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm ⋮ Nonconvex TGV regularization model for multiplicative noise removal with spatially varying parameters ⋮ A convex total generalized variation regularized model for multiplicative noise and blur removal ⋮ Second order total generalized variation for Speckle reduction in ultrasound images ⋮ Multiplicative noise removal based on the linear alternating direction method for a hybrid variational model ⋮ A new variational approach for restoring images with multiplicative noise ⋮ Total generalized variation denoising of speckled images using a primal-dual algorithm

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