A regularization parameter selection model for total variation based image noise removal

Noise Removal ◽

Parameter Selection ◽

Image Noise ◽

Selection Model ◽

Automatic regularization parameter selection by generalized cross-validation for total variational Poisson noise removal

Applied Optics ◽

10.1364/ao.56.000d47 ◽

2017 ◽

Vol 56 (9) ◽

pp. D47 ◽

Cited By ~ 10

Author(s):

Xiongjun Zhang ◽

Bahram Javidi ◽

Michael K. Ng

Keyword(s):

Cross Validation ◽

Noise Removal ◽

Parameter Selection ◽

Poisson Noise ◽

Generalized Cross Validation ◽

Lecture Notes in Computer Science - Scale Space and Variational Methods in Computer Vision ◽

Multi-scale Total Variation with Automated Regularization Parameter Selection for Color Image Restoration

10.1007/978-3-642-02256-2_23 ◽

2009 ◽

pp. 271-281 ◽

Cited By ~ 11

Author(s):

Yiqiu Dong ◽

Michael Hintermüller

Keyword(s):

Image Restoration ◽

Total Variation ◽

Color Image ◽

Parameter Selection ◽

Multi Scale ◽

Selection For ◽

Total Variation Regularized SENSE Image Reconstruction Based on Improved regularization parameter selection

10.1109/ccdc52312.2021.9602165 ◽

2021 ◽

Author(s):

Chunli Wu ◽

Zhiming Bai

Keyword(s):

Image Reconstruction ◽

Total Variation ◽

Parameter Selection ◽

Automated Regularization Parameter Selection in Multi-Scale Total Variation Models for Image Restoration

Journal of Mathematical Imaging and Vision ◽

10.1007/s10851-010-0248-9 ◽

2010 ◽

Vol 40 (1) ◽

pp. 82-104 ◽

Cited By ~ 86

Author(s):

Yiqiu Dong ◽

Michael Hintermüller ◽

M. Monserrat Rincon-Camacho

Keyword(s):

Image Restoration ◽

Total Variation ◽

Parameter Selection ◽

Multi Scale ◽

Lecture Notes in Electrical Engineering - Advanced Multimedia and Ubiquitous Engineering ◽

Spectral Response Based Regularization Parameter Selection for Total Variation Image Restoration

10.1007/978-981-10-5041-1_101 ◽

2017 ◽

pp. 640-645

Author(s):

Yuhui Zheng ◽

Min Li ◽

Kai Ma ◽

Shunfeng Wang ◽

Jin Wang

Keyword(s):

Image Restoration ◽

Total Variation ◽

Spectral Response ◽

Parameter Selection ◽

Selection For ◽

Regularization parameter selection and an efficient algorithm for total variation-regularized positron emission tomography

Numerical Algorithms ◽

10.1007/s11075-010-9427-4 ◽

2010 ◽

Vol 57 (2) ◽

pp. 255-271 ◽

Cited By ~ 8

Author(s):

Johnathan M. Bardsley ◽

John Goldes

Keyword(s):

Positron Emission Tomography ◽

Total Variation ◽

Efficient Algorithm ◽

Parameter Selection ◽

Emission Tomography ◽

Positron Emission ◽

Scale Recognition, Regularization Parameter Selection, and Meyer's G Norm in Total Variation Regularization

Multiscale Modeling and Simulation ◽

10.1137/040621624 ◽

2006 ◽

Vol 5 (1) ◽

pp. 273-303 ◽

Cited By ~ 49

Author(s):

David M. Strong ◽

Jean-François Aujol ◽

Tony F. Chan

Keyword(s):

Total Variation ◽

Parameter Selection ◽

Total Variation Regularization ◽

An automatic regularization parameter selection algorithm in the total variation model for image deblurring

Numerical Algorithms ◽

10.1007/s11075-013-9775-y ◽

2013 ◽

Vol 67 (1) ◽

pp. 73-92 ◽

Cited By ~ 16

Author(s):

K. Chen ◽

E. Loli Piccolomini ◽

F. Zama

Keyword(s):

Total Variation ◽

Image Deblurring ◽

Parameter Selection ◽

Selection Algorithm ◽

Total Variation Model ◽

Regularization Parameter Selection ◽

Variation Model

$ \chi^2 $ test for total variation regularization parameter selection

Inverse Problems & Imaging ◽

10.3934/ipi.2020019 ◽

2020 ◽

Vol 14 (3) ◽

pp. 401-421

Author(s):

J. Mead ◽

Keyword(s):

Total Variation ◽

Parameter Selection ◽

Total Variation Regularization ◽

Regularization Parameter Selection for Total Variation Model Based on Local Spectral Response

Journal of Information Processing Systems ◽

10.3745/jips.02.0072 ◽

2017 ◽

Author(s):

Yuhui Zheng ◽

Kai Ma ◽

Qiqiong Yu ◽

Jianwei Zhang ◽

Jin Wang

Keyword(s):

Total Variation ◽

Spectral Response ◽

Parameter Selection ◽

Model Based ◽

Total Variation Model ◽

Selection For ◽

Regularization Parameter Selection ◽

Variation Model