High-order total variation-based multiplicative noise removal with spatially adapted parameter selection-Reference-Cited by-同舟云学术

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High-order total variation-based multiplicative noise removal with spatially adapted parameter selection

Published:2013-09-10 Issue:10 Volume:30 Page:1956
ISSN:1084-7529
Container-title:Journal of the Optical Society of America A
language:en
Short-container-title:J. Opt. Soc. Am. A

Author:

Liu Jun,Huang Ting-Zhu,Xu Zongben,Lv Xiao-Guang

Funder

973 Program

NSFC

Chinese Universities Specialized Research Fund for the Doctoral Program

Sichuan Province Sci. and Tech. Research

Publisher

The Optical Society

Subject

Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference30 articles.

1. De-noising by soft-thresholding

2. A Fast Spectral Method for Active 3D Shape Reconstruction

3. A Review of Image Denoising Algorithms, with a New One

4. General Bayesian estimation for speckle noise reduction in optical coherence tomography retinal imagery

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1. Multiplicative noise removal using complementary total generalized variation and nonlocal low rank regularization;Optik;2023-11

2. An adaptive image restoration algorithm based on hybrid total variation regularization;Turkish Journal of Electrical Engineering and Computer Sciences;2023-01-01

3. Image Restoration using Nonlocal Regularized Variational Model with Spatially Adapted Regularization Parameter;Mathematical Problems in Engineering;2022-06-15

4. A spatially adaptive hybrid total variation model for image restoration under Gaussian plus impulse noise;Applied Mathematics and Computation;2022-04

5. 3-D Gabor-based anisotropic diffusion for speckle noise suppression in dynamic ultrasound images;Physical and Engineering Sciences in Medicine;2021-01-26

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