5.3.9.2 Poisson Noise Removal

Chapter Contents (Back)
Noise Removal. Poisson Noise. Denoising.

Rabbani, M.,
Bayesian Filtering of Poisson Noise Using Local Statistics,
ASSP(36), 1988, pp. 933-937. BibRef 8800

Lasota, S.[Slawomir], Niemiro, W.[Wojciech],
A version of the Swendsen-Wang algorithm for restoration of images degraded by Poisson noise,
PR(36), No. 4, April 2003, pp. 931-941.
Elsevier DOI 0304

See also Positron emission tomography by Markov chain Monte Carlo with auxiliary variables. BibRef

Lu, H., Kim, Y., Anderson, J.M.M.,
Improved Poisson Intensity Estimation: Denoising Application Using Poisson Data,
IP(13), No. 8, August 2004, pp. 1128-1135.
IEEE DOI 0409
BibRef

Le, T.[Triet], Chartrand, R.[Rick], Asaki, T.J.[Thomas J.],
A Variational Approach to Reconstructing Images Corrupted by Poisson Noise,
JMIV(27), No. 3, April 2007, pp. 257-263.
Springer DOI 0704
BibRef

Dupe, F.X., Fadili, J.M., Starck, J.L.,
A Proximal Iteration for Deconvolving Poisson Noisy Images Using Sparse Representations,
IP(18), No. 2, February 2009, pp. 310-321.
IEEE DOI 0901
BibRef

Lefkimmiatis, S.[Stamatios], Maragos, P.[Petros], Papandreou, G.[George],
Bayesian Inference on Multiscale Models for Poisson Intensity Estimation: Applications to Photon-Limited Image Denoising,
IP(18), No. 8, August 2009, pp. 1724-1741.
IEEE DOI 0907
BibRef
And: A1, A3, A2:
Poisson-Haar Transform: A nonlinear multiscale representation for photon-limited image denoising,
ICIP09(3853-3856).
IEEE DOI 0911
BibRef
Earlier: A1, A3, A2:
Photon-limited image denoising by inference on multiscale models,
ICIP08(2332-2335).
IEEE DOI 0810
BibRef
Earlier: A3, A2, Only:
A Cross-Validatory Statistical Approach to Scale Selection for Image Denoising by Nonlinear Diffusion,
CVPR05(I: 625-630).
IEEE DOI 0507
BibRef
And: A3, A2, Only:
Image Denoising in Nonlinear Scale-Spaces: Automatic Scale Selection via Cross-Validation,
ICIP05(I: 481-484).
IEEE DOI 0512
BibRef

Lefkimmiatis, S.[Stamatios], Bourquard, A., Unser, M.,
Hessian-Based Norm Regularization for Image Restoration With Biomedical Applications,
IP(21), No. 3, March 2012, pp. 983-995.
IEEE DOI 1203
BibRef

Lefkimmiatis, S.[Stamatios], Unser, M.,
Poisson Image Reconstruction With Hessian Schatten-Norm Regularization,
IP(22), No. 11, 2013, pp. 4314-4327.
IEEE DOI 1310
ADMM BibRef

Makitalo, M., Foi, A.,
Optimal Inversion of the Anscombe Transformation in Low-Count Poisson Image Denoising,
IP(20), No. 1, January 2011, pp. 99-109.
IEEE DOI 1101
BibRef
Earlier:
On the inversion of the Anscombe transformation in low-count Poisson image denoising,
LNLA09(26-32).
IEEE DOI 0908
BibRef

Makitalo, M., Foi, A.,
A Closed-Form Approximation of the Exact Unbiased Inverse of the Anscombe Variance-Stabilizing Transformation,
IP(20), No. 9, September 2011, pp. 2697-2698.
IEEE DOI 1109
BibRef

Makitalo, M., Foi, A.,
Optimal Inversion of the Generalized Anscombe Transformation for Poisson-Gaussian Noise,
IP(22), No. 1, January 2013, pp. 91-103.
IEEE DOI 1301
BibRef

Makitalo, M., Foi, A.,
Noise Parameter Mismatch in Variance Stabilization, With an Application to Poisson-Gaussian Noise Estimation,
IP(23), No. 12, December 2014, pp. 5348-5359.
IEEE DOI 1402
Gaussian noise BibRef

Luisier, F., Blu, T., Unser, M.,
Image Denoising in Mixed Poisson-Gaussian Noise,
IP(20), No. 3, March 2011, pp. 696-708.
IEEE DOI 1103
BibRef

Chen, D.Q.[Dai-Qiang], Cheng, L.Z.[Li-Zhi],
Deconvolving Poissonian images by a novel hybrid variational model,
JVCIR(22), No. 7, October 2011, pp. 643-652.
Elsevier DOI 1109
Total variation; Frame coefficients; Split Bregman method; Douglas-Rachford splitting; Poisson noise; Maximum a posteriori estimator; Hybrid model; Image deconvolution BibRef

Harmany, Z.T.[Zachary T.], Marcia, R.F.[Roummel F.], Willett, R.M.[Rebecca M.],
This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms: Theory and Practice,
IP(21), No. 3, March 2012, pp. 1084-1096.
IEEE DOI 1203
BibRef
Earlier: A3, A1, A2:
Poisson image reconstruction with total variation regularization,
ICIP10(4177-4180).
IEEE DOI 1009
BibRef

Harmany, Z.T.[Zachary T.], Thompson, D.[Daniel], Willett, R.M.[Rebecca M.], Marcia, R.F.[Roummel F.],
Gradient projection for linearly constrained convex optimization in sparse signal recovery,
ICIP10(3361-3364).
IEEE DOI 1009
BibRef

Lee, C.[Chul], Lee, C.[Chulwoo], Kim, C.S.[Chang-Su],
An MMSE approach to nonlocal image denoising: Theory and practical implementation,
JVCIR(23), No. 3, April 2012, pp. 476-490.
Elsevier DOI 1203
BibRef
Earlier:
MMSE nonlocal means denoising algorithm for Poisson noise removal,
ICIP11(2561-2564).
IEEE DOI 1201
Image denoising; Nonlocal means filter; Minimum mean square error (MMSE) denoising; Bayesian estimation; Noisy nonlocal neighbors; Probabilistic tree search; External database; Image restoration BibRef

Srivastava, R.[Rajeev], Srivastava, S.[Subodh],
Restoration of Poisson noise corrupted digital images with nonlinear PDE based filters along with the choice of regularization parameter estimation,
PRL(34), No. 10, 15 July 2013, pp. 1175-1185.
Elsevier DOI 1306
Image restoration; PDE based filters; Variational framework; Regularization functions; Regularization parameter selection; Generalized cross validations BibRef

Ma, L.Y.[Li-Yan], Moisan, L., Yu, J.[Jian], Zeng, T.Y.[Tie-Yong],
A Dictionary Learning Approach for Poisson Image Deblurring,
MedImg(32), No. 7, 2013, pp. 1277-1289.
IEEE DOI 1307
Poisson distribution BibRef

Bindilatti, A.A., Mascarenhas, N.D.A.,
A Nonlocal Poisson Denoising Algorithm Based on Stochastic Distances,
SPLetters(20), No. 11, 2013, pp. 1010-1013.
IEEE DOI 1310
Poisson distribution BibRef

Evangelista, R.C.[Rodrigo C.], Salvadeo, D.H.P.[Denis H.P.], Mascarenhas, N.D.A.[Nelson D.A.],
A new bayesian Poisson denoising algorithm based on nonlocal means and stochastic distances,
PR(122), 2022, pp. 108363.
Elsevier DOI 2112
Poisson denoising, Nonlocal means, Stochastic distances, Bayesian estimation, Conjugate distributions, Low dose CT BibRef

Salmon, J.[Joseph], Harmany, Z.[Zachary], Deledalle, C.A.[Charles-Alban], Willett, R.[Rebecca],
Poisson Noise Reduction with Non-local PCA,
JMIV(48), No. 2, February 2014, pp. 279-294.
Springer DOI 1402
BibRef

Salvadeo, D.H.P.[Denis H.P.], Bloch, I.[Isabelle], Tupin, F.[Florence], Mascarenhas, N.D.A.[Nelson D.A.], Levada, A.L.M.[Alexandre L.M.], Deledalle, C.A.[Charles-Alban], Dahdouh, S.[Sonia],
Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions,
ICIP14(2699-2703)
IEEE DOI 1502
Equations BibRef

Deledalle, C.A.[Charles-Alban], Salmon, J.[Joseph], Dalalyan, A.S.[Arnak S.],
Image denoising with patch based PCA: local versus global,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Le Montagner, Y., Angelini, E.D., Olivo-Marin, J.C.,
An Unbiased Risk Estimator for Image Denoising in the Presence of Mixed Poisson-Gaussian Noise,
IP(23), No. 3, March 2014, pp. 1255-1268.
IEEE DOI 1403
BibRef
And: Erratum: IP(23), No. 6, June 2014, pp. 2750-2750.
IEEE DOI 1406
Biomedical optical imaging Gaussian noise BibRef

Jin, X.D.[Xiao-Dan], Xu, Z.Y.[Zhen-Yu], Hirakawa, K.,
Noise Parameter Estimation for Poisson Corrupted Images Using Variance Stabilization Transforms,
IP(23), No. 3, March 2014, pp. 1329-1339.
IEEE DOI 1403
Poisson distribution BibRef

Chen, D.,
Regularized Generalized Inverse Accelerating Linearized Alternating Minimization Algorithm for Frame-Based Poissonian Image Deblurring,
SIIMS(7), No. 2, 2014, pp. 716-739.
DOI Link 1405
BibRef

Giryes, R.[Raja], Elad, M.[Michael],
Sparsity-Based Poisson Denoising With Dictionary Learning,
IP(23), No. 12, December 2014, pp. 5057-5069.
IEEE DOI 1402
BibRef
And:
Sparsity based poisson inpainting,
ICIP14(2839-2843)
IEEE DOI 1502
Approximation methods Gaussian noise BibRef

Giryes, R.[Raja], Elad, M.[Michael], Bruckstein, A.M.,
Sparsity Based Methods for Overparameterized Variational Problems,
SIIMS(8), No. 3, 2015, pp. 2133-2159.
DOI Link 1511
BibRef

Dar, Y., Bruckstein, A.M., Elad, M., Giryes, R.[Raja],
Postprocessing of Compressed Images via Sequential Denoising,
IP(25), No. 7, July 2016, pp. 3044-3058.
IEEE DOI 1606
data compression BibRef

Dar, Y., Elad, M., Bruckstein, A.M.,
Compression for Multiple Reconstructions,
ICIP18(440-444)
IEEE DOI 1809
Image coding, Optimization, Standards, Image reconstruction, Rate-distortion, Distortion, Rendering (computer graphics), alternating direction method of multipliers (ADMM) BibRef

Dar, Y., Elad, M., Bruckstein, A.M.,
Optimized Pre-Compensating Compression,
IP(27), No. 10, October 2018, pp. 4798-4809.
IEEE DOI 1808
data compression, distortion, image restoration, liquid crystal displays, video coding, alternating direction method of multipliers (ADMM) BibRef

Remez, T., Litany, O., Giryes, R.[Raja], Bronstein, A.M.,
Deep class-aware image denoising,
ICIP17(1895-1899)
IEEE DOI 1803
Convolutional codes, Face, Image denoising, Noise measurement, Noise reduction, Semantics, Training, Image denoising, machine learning BibRef

Wang, L.M.[Li-Ming], Huang, J.J.[Jia-Ji], Yuan, X.[Xin], Krishnamurthy, K.[Kalyani], Greenberg, J.[Joel], Cevher, V.[Volkan], Rodrigues, M.R.D.[Miguel R.D.], Brady, D.[David], Calderbank, R.[Robert], Carin, L.[Lawrence],
Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements,
SIIMS(8), No. 3, 2015, pp. 1923-1954.
DOI Link 1511
BibRef

Mahabadi, R.K., Lin, J., Cevher, V.,
A Learning-Based Framework for Quantized Compressed Sensing,
SPLetters(26), No. 6, June 2019, pp. 883-887.
IEEE DOI 1906
compressed sensing, quantisation (signal), signal reconstruction, signal sampling, BPDQ, measurements number, sampling pattern BibRef

Mansouri, A.[Alamin], Deger, F.[Ferdinand], Pedersen, M.[Marius], Hardeberg, J.Y.[Jon Y.], Voisin, Y.[Yvon],
An adaptive spatial-spectral total variation approach for Poisson noise removal in hyperspectral images,
SIViP(10), No. 3, March 2016, pp. 447-454.
Springer DOI 1602
BibRef

Azzari, L., Foi, A.,
Variance Stabilization for Noisy+Estimate Combination in Iterative Poisson Denoising,
SPLetters(23), No. 8, August 2016, pp. 1086-1090.
IEEE DOI 1608
Poisson distribution BibRef

Rakhshanfar, M., Amer, M.A.,
Estimation of Gaussian, Poissonian: Gaussian, and Processed Visual Noise and Its Level Function,
IP(25), No. 9, September 2016, pp. 4172-4185.
IEEE DOI 1609
Gaussian noise BibRef

Rond, A.[Arie], Giryes, R.[Raja], Elad, M.[Michael],
Poisson inverse problems by the Plug-and-Play scheme,
JVCIR(41), No. 1, 2016, pp. 96-108.
Elsevier DOI 1612
Award, JVCI, HM. Poisson denoising BibRef

Wang, W.[Wei], He, C.J.[Chuan-Jiang],
A Fast and Effective Algorithm for a Poisson Denoising Model With Total Variation,
SPLetters(24), No. 3, March 2017, pp. 269-273.
IEEE DOI 1702
Extraterrestrial measurements BibRef

Chen, D.Q.[Dai-Qiang],
Inexact alternating direction method based on Newton descent algorithm with application to Poisson image deblurring,
SIViP(11), No. 1, January 2017, pp. 89-96.
Springer DOI 1702
BibRef

Tan, X.[Xin], Liu, Y.[Yu], Zuo, C.L.[Cheng-Lin], Zhang, M.J.[Mao-Jun],
A real-time video denoising algorithm with FPGA implementation for Poisson-Gaussian noise,
RealTimeIP(13), No. 2, June 2017, pp. 327-343.
WWW Link. 1708
BibRef

Li, W.L.[Wei-Li], Yin, X.Q.[Xiao-Qing], Liu, Y.[Yu], Zhang, M.J.[Mao-Jun],
Robust video denoising for mixed Poisson, Gaussian and impule noise,
ICIVC17(459-462)
IEEE DOI 1708
Acceleration, Image restoration, Mathematical model, Nickel, Noise reduction, Optimization, Robustness, low rank, mixed noises, robust, sparse, video, denoising BibRef

Tan, H.L.[Han-Lin], Liu, Y.[Yu], Zhang, M.J.[Mao-Jun],
Noise2Variance: Dual networks with variance constraint for self-supervised real-world image denoising,
IET-IPR(18), No. 12, 2024, pp. 3251-3261.
DOI Link 2411
convolutional neural nets, image denoising, unsupervised learning BibRef

Chang, H.B.[Hui-Bin], Lou, Y.F.[Yi-Fei], Duan, Y.P.[Yu-Ping], Marchesini, S.[Stefano],
Total Variation-Based Phase Retrieval for Poisson Noise Removal,
SIIMS(11), No. 1, 2018, pp. 24-55.
DOI Link 1804
BibRef

Chang, H.B.[Hui-Bin], Marchesini, S.[Stefano], Lou, Y.F.[Yi-Fei], Zeng, T.Y.[Tie-Yong],
Variational Phase Retrieval with Globally Convergent Preconditioned Proximal Algorithm,
SIIMS(11), No. 1, 2018, pp. 56-93.
DOI Link 1804
BibRef

di Martino, M.[Matías], Facciolo, G.[Gabriele],
An Analysis and Implementation of Multigrid Poisson Solvers With Verified Linear Complexity,
IPOL(8), 2018, pp. 192-218.
DOI Link 1808
Code, Poisson Solver. BibRef

Wang, C.[Cong], Yang, J.B.[Jian-Bin],
Poisson noise removal of images on graphs using tight wavelet frames,
VC(34), No. 10, October 2018, pp. 1357-1369.
WWW Link. 1809
BibRef

Remez, T., Litany, O., Giryes, R., Bronstein, A.M.,
Class-Aware Fully Convolutional Gaussian and Poisson Denoising,
IP(27), No. 11, November 2018, pp. 5707-5722.
IEEE DOI 1809
Noise reduction, Image denoising, Convolution, Noise measurement, Training, Neural networks, Face, Image denoising, Gaussian noise, class-aware denoising BibRef

Jin, Q.Y.[Qi-Yu], Miyashita, O.[Osamu], Tama, F.[Florence], Yang, J.[Jie], Jonic, S.[Slavica],
Poisson image denoising by piecewise principal component analysis and its application in single-particle X-ray diffraction imaging,
IET-IPR(12), No. 12, December 2018, pp. 2264-2274.
DOI Link 1812
BibRef

Zhu, X.L.[Xiao-Long], Feng, X.C.[Xiang-Chu], Wang, W.W.[Wei-Wei], Jia, X.X.[Xi-Xi], Zhang, R.[Rui], He, R.Q.[Rui-Qiang], Xu, C.[Chen],
HCLR: A hybrid clustering and low-rank regularization-based method for photon-limited image restoration,
JVCIR(57), 2018, pp. 61-68.
Elsevier DOI 1812
Image restoration, Low rank, Poisson denoising, Newton's method BibRef

Su, Y.M.[Yue-Ming], Lian, Q.S.[Qiu-Sheng], Zhang, X.H.[Xiao-Hua], Shi, B.S.[Bao-Shun], Fan, X.Y.[Xiao-Yu],
Multi-scale Cross-path Concatenation Residual Network for Poisson denoising,
IET-IPR(13), No. 8, 20 June 2019, pp. 1295-1303.
DOI Link 1906
BibRef

Zhang, M.H.[Ming-Hui], Zhang, F.Q.[Feng-Qin], Liu, Q.[Qiegen], Wang, S.S.[Shan-Shan],
VST-Net: Variance-stabilizing transformation inspired network for Poisson denoising,
JVCIR(62), 2019, pp. 12-22.
Elsevier DOI 1908
Poisson noise reduction, Deep learning, Variance-stabilizing transformation, Joint learning, Two-stage learning BibRef

Sun, K.[Kaicong], Tran, T.H.[Trung-Hieu], Krawtschenko, R.[Roman], Simon, S.[Sven],
Multi-frame super-resolution reconstruction based on mixed Poisson-Gaussian noise,
SP:IC(82), 2020, pp. 115736.
Elsevier DOI 2001
Super-resolution, Mixed Poisson-Gaussian noise, Statistical image reconstruction BibRef

Khoa Phan, T.D., Tran, T.H.Y.[T. H. Yen],
A Space-Variant Nonlinear Algorithm for Denoising Omnidirectional Images Corrupted by Poisson Noise,
SPLetters(27), 2020, pp. 535-539.
IEEE DOI 2005
Noise reduction, Cameras, Image resolution, TV, Mirrors, Biological system modeling, Adaptation models, Image denoising, Poisson noise BibRef

Zhao, Z., Liu, L.T., Singer, A.,
Steerable ePCA: Rotationally Invariant Exponential Family PCA,
IP(29), 2020, pp. 6069-6081.
IEEE DOI 2005
Poisson noise, X-ray free electron laser, steerable PCA, eigenvalue shrinkage, autocorrelation analysis, image denoising BibRef

Marmin, A., Jezierska, A., Castella, M., Pesquet, J.,
Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise,
SPLetters(27), 2020, pp. 970-974.
IEEE DOI 2007
Optimization, Gaussian noise, Computational modeling, Numerical models, Convolution, Minimization, Complexity theory, Padé approximation BibRef

Bobin, J., Hamzaoui, I.E., Picquenot, A., Acero, F.,
Sparse BSS From Poisson Measurements,
IP(29), 2020, pp. 9429-9444.
IEEE DOI 1806
Approximation algorithms, Extraterrestrial measurements, Additives, Noise measurement, Robustness, Mixture models, Poisson measurements BibRef

Ghulyani, M., Arigovindan, M.,
Fast Roughness Minimizing Image Restoration Under Mixed Poisson-Gaussian Noise,
IP(30), 2021, pp. 134-149.
IEEE DOI 2011
Image restoration, Noise measurement, Extraterrestrial measurements, Convergence, Minimization, regularization BibRef

Rasal, T.[Tushar], Veerakumar, T.[Thangaraj], Subudhi, B.N.[Badri Narayan], Esakkirajan, S.[Sankaralingam],
Mixed Poisson Gaussian noise reduction in fluorescence microscopy images using modified structure of wavelet transform,
IET-IPR(15), No. 7, 2021, pp. 1383-1398.
DOI Link 2106
BibRef

Bähler, N.[Nicolas], El Helou, M.[Majed], Objois, É.[Étienne], Okumus, K.[Kaan], Süsstrunk, S.[Sabine],
PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples,
SPLetters(29), 2022, pp. 2602-2606.
IEEE DOI 2301
Noise measurement, Mathematical models, Noise reduction, Analytical models, Training, Reactive power, Neural networks, Poisson-Gaussian noise modeling BibRef

Chen, M.[Miao], Wen, M.[Meng], Tang, Y.C.[Yu-Chao],
First-order primal-dual algorithm for image restoration corrupted by mixed Poisson-Gaussian noise,
SP:IC(117), 2023, pp. 117012.
Elsevier DOI 2308
Mixed Poisson-Gaussian noise, Primal-dual algorithm, Kullback-Leibler divergence, Total variation BibRef

Liang, H.[Hao], Liu, R.[Rui], Wang, Z.Y.[Zhong-Yuan], Ma, J.Y.[Jia-Yi], Tian, X.[Xin],
Variational Bayesian deep network for blind Poisson denoising,
PR(143), 2023, pp. 109810.
Elsevier DOI 2310
Blind poisson denoising, Variational bayesian, Parameter estimation BibRef

Chen, Q.Q.[Qiu-Qiu], Xing, Y.Y.X.[Yuan-Yan-Xiu], Song, L.L.[Lin-Lin],
Neighbor2Global: Self-supervised image denoising for Poisson-Gaussian noise,
JVCIR(98), 2024, pp. 104049.
Elsevier DOI 2402
Image denoising, Self-supervised training, GAT, Image fusion BibRef

Wu, D.[Delong], Zhu, H.[Hao], Zhang, Q.[Qi], Li, Y.[You], Ma, Z.[Zhan], Cao, X.[Xun],
Neural Poisson Solver: A Universal and Continuous Framework for Natural Signal Blending,
ECCV24(LXXX: 259-275).
Springer DOI 2412
BibRef

Bui, K.[Kevin], Lou, Y.F.[Yi-Fei], Park, F.[Fredrick], Xin, J.[Jack],
Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising,
ICIP23(1020-1024)
IEEE DOI 2312
BibRef

Byun, J.[Jaeseok], Cha, S.[Sungmin], Moon, T.[Taesup],
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise,
CVPR21(5764-5773)
IEEE DOI 2111
Training, Noise reduction, Neural networks, Estimation, Benchmark testing BibRef

Khademi, W.[Wesley], Rao, S.[Sonia], Minnerath, C.[Clare], Hagen, G.[Guy], Ventura, J.[Jonathan],
Self-Supervised Poisson-Gaussian Denoising,
WACV21(2130-2138)
IEEE DOI 2106
Training, Adaptation models, Microscopy, Noise reduction, Data models, Noise measurement BibRef

Zha, R., Zhang, J., Wei, Z.,
Multi-Components Low Dimensional Manifold Model For Photonlimited Poisson Noisy Image Reconstruction,
ICIP19(1134-1137)
IEEE DOI 1910
Poisson reconstruction, image components, low dimensional manifold model, regularization BibRef

Tsutake, C., Yoshida, T.,
Reduction of Poisson Noise in Coded Exposure Photography,
ICIP18(3938-3942)
IEEE DOI 1809
Discrete Fourier transforms, Lighting, Photography, Photonics, Image sensors, Compressed sensing, Image coding, image recovery, compressed sensing BibRef

Yang, Q., Jung, C., Fu, Q., Song, H.,
Low Light Image Denoising Based on Poisson Noise Model and Weighted TV Regularization,
ICIP18(3199-3203)
IEEE DOI 1809
TV, Noise reduction, Image denoising, Image edge detection, Photonics, Smoothing methods, Image restoration, Denoising, total variation BibRef