5.3.13 Restoration by Deconvolution, Blind Deconvolution

Yuan, S., Wang, S., Ma, M., Ji, Y., Deng, L.,
Sparse Bayesian Learning-Based Time-Variant Deconvolution,
GeoRS(55), No. 11, November 2017, pp. 6182-6194.
IEEE DOI 1711
Attenuation, Bayes methods, Convolution, Deconvolution, Time-frequency analysis, Attenuation, Bayesian framework, inverse problems, sparse Bayesian learning (SBL), BibRef

Li, J., Luisier, F., Blu, T.,
PURE-LET Image Deconvolution,
IP(27), No. 1, January 2018, pp. 92-105.
IEEE DOI 1712
BibRef
Earlier:
Deconvolution of poissonian images with the PURE-LET approach,
ICIP16(2708-2712)
IEEE DOI 1610
Gaussian noise, Haar transforms, Wiener filters, deconvolution, image restoration, image segmentation, mean square error methods, unbiased risk estimate BibRef

Ren, D., Zuo, W., Zhang, D., Xu, J., Zhang, L.,
Partial Deconvolution With Inaccurate Blur Kernel,
IP(27), No. 1, January 2018, pp. 511-524.
IEEE DOI 1712
Computational modeling, Deconvolution, Estimation error, Kernel, Robustness, E-M algorithm, Image deblurring, blind deconvolution, blur kernel estimation BibRef

Gabarda, S.[Salvador], Cristóbal, G.[Gabriel], Goel, N.[Navdeep],
Anisotropic blind image quality assessment: Survey and analysis with current methods,
JVCIR(52), 2018, pp. 101-105.
Elsevier DOI 1804
Image quality assessment, Pseudo-Wigner distribution, Rényi entropy, Anisotropy, Correlation, Mean opinion scores BibRef

Carrasquinha, E.[Eunice], Amado, C.[Conceição], Pires, A.M.[Ana M.], Oliveira, L.[Lina],
Image reconstruction based on circulant matrices,
SP:IC(63), 2018, pp. 72-80.
Elsevier DOI 1804
PCA, Signal processing, Image reconstruction, Circulant matrices, Toeplitz matrices BibRef

Wang, R., Tao, D.,
Training Very Deep CNNs for General Non-Blind Deconvolution,
IP(27), No. 6, June 2018, pp. 2897-2910.
IEEE DOI 1804
Computational modeling, Convolution, Deconvolution, Image restoration, Kernel, Task analysis, Training, Deep CNNs, residual learning BibRef

Han, J., Song, K.S., Kim, J., Kang, M.G.,
Permuted Coordinate-Wise Optimizations Applied to Lp-Regularized Image Deconvolution,
IP(27), No. 7, July 2018, pp. 3556-3570.
IEEE DOI 1805
Cost function, Deconvolution, Estimation, Iterative methods, Kernel, Linear programming, Lp-norm, Non-blind deconvolution, total variation BibRef

Lamash, Y.[Yechiel],
Algorithm and Constraints for Exact Non-blind Deconvolution,
JMIV(60), No. 5, June 2018, pp. 692-706.
WWW Link. 1806
BibRef

Winkler, J.R.[Joab R.], Halawani, H.[Hanan],
The Sylvester and Bézout Resultant Matrices for Blind Image Deconvolution,
JMIV(60), No. 8, October 2018, pp. 1284-1305.
Springer DOI 1810
BibRef

Huang, W., Hand, P.,
Blind Deconvolution by a Steepest Descent Algorithm on a Quotient Manifold,
SIIMS(11), No. 4, 2018, pp. 2757-2785.
DOI Link 1901
BibRef

Gong, D.[Dong], Tan, M.K.[Ming-Kui], Shi, Q.F.[Qin-Feng], van den Hengel, A.J.[Anton J.], Zhang, Y.N.[Yan-Ning],
MPTV: Matching Pursuit-Based Total Variation Minimization for Image Deconvolution,
IP(28), No. 4, April 2019, pp. 1851-1865.
IEEE DOI 1901
BibRef
Earlier: A1, A2, A5, A4, A3:
Self-Paced Kernel Estimation for Robust Blind Image Deblurring,
ICCV17(1670-1679)
IEEE DOI 1802
BibRef
Earlier: A1, A2, A5, A4, A3:
Blind Image Deconvolution by Automatic Gradient Activation,
CVPR16(1827-1836)
IEEE DOI 1612
convex programming, deconvolution, gradient methods, image denoising, image reconstruction, convex programming. estimation theory, image enhancement, image restoration, learning (artificial intelligence), Robustness BibRef

Boudjenouia, F.[Fouad], Abed-Meraim, K.[Karim], Chetouani, A.[Aladine], Jennane, R.[Rachid],
Robust, blind multichannel image identification and restoration using stack decoder,
IET-IPR(13), No. 3, February 2019, pp. 475-482.
DOI Link 1903
BibRef

Abbass, M.Y., Kim, H.[HyungWon], Abdelwahab, S.A.[Safey A.], Haggag, S.S., El-Rabaie, E.S.M.[El-Sayed M.], Dessouky, M.I.[Moawad I.], El-Samie, F.E.A.[Fathi E. Abd],
Image deconvolution using homomorphic technique,
SIViP(13), No. 4, June 2019, pp. 703-709.
Springer DOI 1906
BibRef

Xue, F.[Feng], Liu, J.[Jiaqi], Ai, X.[Xia],
Parametric PSF estimation based on predicted-SURE with l1-penalized sparse deconvolution,
SIViP(13), No. 4, June 2019, pp. 635-642.
WWW Link. 1906
BibRef

Siadat, M., Aghazadeh, N., Akbarifard, F., Brismar, H., Öktem, O.,
Joint Image Deconvolution and Separation Using Mixed Dictionaries,
IP(28), No. 8, August 2019, pp. 3936-3945.
IEEE DOI 1907
deconvolution, image reconstruction, image representation, iterative methods, synthetic data, wavelets BibRef

Hajmohammadi, S.[Solmaz], Nooshabadi, S.[Saeid], Archer, G.E.[Glen E.], Bos, J.P., Struther, A.[Allan],
Parallel hybrid bispectrum-multi-frame blind deconvolution image reconstruction technique,
RealTimeIP(16), No. 4, August 2019, pp. 919-929.
Springer DOI 1908
BibRef

Güngör, A., Kar, O.F.,
A Transform Learning Based Deconvolution Technique with Super-Resolution and Microscanning Applications,
ICIP19(2159-2163)
IEEE DOI 1910
Deconvolution, Sparsity, Transform Learning, Computational Imaging, Super-Resolution BibRef

Ancora, D., Bassi, A.,
Deconvolved Image Restoration From Auto-Correlations,
IP(30), 2021, pp. 1332-1341.
IEEE DOI 2012
Image reconstruction, Kernel, Imaging, Correlation, Extraterrestrial measurements, Deconvolution, Convolution, inverse problem BibRef

Zhang, Y., Lau, Y., Kuo, H.W., Cheung, S., Pasupathy, A., Wright, J.,
On the Global Geometry of Sphere-Constrained Sparse Blind Deconvolution,
PAMI(43), No. 3, March 2021, pp. 999-1008.
IEEE DOI 2102
BibRef
Earlier: CVPR17(4381-4389)
IEEE DOI 1711
Convolution, Deconvolution, Kernel, Geometry, Image restoration, Optimization, Microscopy, Image deblurring, blind deconvolution, nonconvex optimization. Convolution, Deconvolution, Geometry, Image restoration, Kernel, Microscopy, Optimization BibRef

Gao, W.Z.[Wei-Zhe], Xu, X.B.[Xue-Bin], Yang, Y.K.[Yi-Kang], Zhang, Z.G.[Zhi-Guang],
Non-iterative blind deconvolution algorithm based on power-law distribution,
IET-IPR(14), No. 17, 24 December 2020, pp. 4499-4506.
DOI Link 2104
BibRef

Tao, S.Y.[Shu-Yin], Dong, W.[Wende], Xu, J.[Jian], Lu, J.F.[Jian-Feng], Xu, G.[Guili], Chen, Y.T.[Yue-Ting],
An adaptive two phase blind image deconvolution algorithm for an iterative regularization model,
JVCIR(81), 2021, pp. 103370.
Elsevier DOI 2112
Blind image deconvolution, -norm gradient regularization, TV regularization BibRef

Liu, J.[Jing], Tan, J.Q.[Jie-Qing], Zhang, L.[Li], Ge, X.Y.[Xian-Yu], Hu, D.D.[Dan-Dan],
Blind deblurring with patch-wise second-order gradient prior,
SP:IC(107), 2022, pp. 116781.
Elsevier DOI 2208
Motion deblurring, Second-order gradient, Kernel similarity, Blind deconvolution, Local image patches BibRef

Liu, J.[Jing], Tan, J.Q.[Jie-Qing], Ge, X.Y.[Xian-Yu], Hu, D.D.[Dan-Dan], He, L.[Lei],
Blind deblurring with fractional-order calculus and local minimal pixel prior,
JVCIR(89), 2022, pp. 103645.
Elsevier DOI 2212
Motion deblurring, Deconvolution, Kernel estimation, Fractional-Order calculus Theory, Local Minimal Pixel Prior BibRef

Wang, W.X.[Wei-Xi], Li, J.[Ji], Ji, H.[Hui],
L_1-Norm Regularization for Short-and-Sparse Blind Deconvolution: Point Source Separability and Region Selection,
SIIMS(15), No. 3, 2022, pp. 1345-1372.
DOI Link 2208
BibRef

Jin, Y.[Yan], Jiang, Z.W.[Zhi-Wei], Xue, Z.Z.[Zhi-Zhong], Hu, Y.B.[Yi-Biao],
Image blind restoration based on degradation representation network,
JVCIR(87), 2022, pp. 103564.
Elsevier DOI 2208
Deep learning, Contrastive learning, Image restoration, Convolution neural network BibRef

Traullé, B.[Benjamin], Bidon, S.[Stéphanie], Roque, D.[Damien],
A Reversible Jump MCMC in Bayesian Blind Deconvolution With a Spherical Prior,
SPLetters(29), 2022, pp. 2372-2376.
IEEE DOI 2212
Bayes methods, Signal processing algorithms, Deconvolution, Space exploration, Monte Carlo methods, Markov processes, von Mises-Fisher prior BibRef

Chen, Z.J.[Zhuo-Jie], Yao, X.[Xin], Xu, Y.[Yong], Wang, J.[Junle], Quan, Y.H.[Yu-Hui],
Unsupervised knowledge transfer for nonblind image deconvolution,
PRL(164), 2022, pp. 232-238.
Elsevier DOI 2212
Nonblind image deconvolution, Deep knowledge transfer, Model adaption, Image recovery BibRef

Huang, Y.S.[Yun-Shi], Chouzenoux, E.[Emilie], Pesquet, J.C.[Jean-Christophe],
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution,
IP(32), 2023, pp. 430-445.
IEEE DOI 2301
Bayes methods, Kernel, Deconvolution, Image restoration, Training, Deep learning, Tuning, Variational Bayesian approach BibRef

Zhao, Y.[Yang], Jia, W.[Wei], Chen, Y.[Yuan], Wang, R.G.[Rong-Gang],
Fast Blind Decontouring Network,
CirSysVideo(33), No. 2, February 2023, pp. 478-490.
IEEE DOI 2302
Task analysis, Image coding, Degradation, Automobiles, Training, Image restoration, Frequency division multiplexing, Decontouring, flat region detection BibRef

Huo, D.[Dong], Masoumzadeh, A.[Abbas], Kushol, R.[Rafsanjany], Yang, Y.H.[Yee-Hong],
Blind Image Deconvolution Using Variational Deep Image Prior,
PAMI(45), No. 10, October 2023, pp. 11472-11483.
IEEE DOI 2310
BibRef

Lyu, Z.[Zhiyu], Chen, Y.[Yan], Sun, H.[Haojun], Hou, Y.M.[Yi-Min],
A dual fusion deep convolutional network for blind universal image denoising,
SP:IC(120), 2024, pp. 117077.
Elsevier DOI 2312
Blind image denoising, Deep convolutional neural network, Non-subsampled shearlet transform, Edge preservation BibRef

Qiao, Y.J.[Yuan-Jian], Shao, M.W.[Ming-Wen], Wang, L.Q.[Lei-Quan], Zuo, W.M.[Wang-Meng],
Learning Depth-Density Priors for Fourier-Based Unpaired Image Restoration,
CirSysVideo(34), No. 4, April 2024, pp. 2604-2618.
IEEE DOI 2404
Degradation, Image restoration, Rain, Visualization, Atmospheric modeling, Rendering (computer graphics), spatial-frequency interaction BibRef

Mbakam, C.K.[Charlesquin Kemajou], Pereyra, M.[Marcelo], Giovannelli, J.F.[Jean-Francois],
Marginal Likelihood Estimation in Semiblind Image Deconvolution: A Stochastic Approximation Approach,
SIIMS(17), No. 2, 2024, pp. 1206-1254.
DOI Link 2407
BibRef

Liu, Y.Q.[Ying-Qi], He, J.W.[Jing-Wen], Liu, Y.H.[Yi-Hao], Lin, X.[Xinqi], Yu, F.[Fanghua], Hu, J.[Jinfan], Qiao, Y.[Yu], Dong, C.[Chao],
AdaptBIR: Adaptive Blind Image Restoration with latent diffusion prior for higher fidelity,
PR(155), 2024, pp. 110659.
Elsevier DOI 2408
Image restoration, Diffusion model, Adaptive adjustment BibRef

Bredell, G.[Gustav], Erdil, E.[Ertunc], Weber, B.[Bruno], Konukoglu, E.[Ender],
Wiener Guided DIP for Unsupervised Blind Image Deconvolution,
WACV23(3046-3055)
IEEE DOI 2302
Deconvolution, Image synthesis, Microscopy, Image edge detection, Distance measurement, Delays, High frequency, Algorithms: Low-level and physics-based vision BibRef

Laribi, G.[Ghada], Welk, M.[Martin],
Towards Quality Assessment of Blind Deconvolution with Shift Compensation,
ICPR22(421-427)
IEEE DOI 2212
Deconvolution, Systematics, Measurement uncertainty, Estimation, Displacement measurement, Time measurement, Image restoration, Fourier method BibRef

Kuo, P.H.[Pin-Hung], Pan, J.S.[Jin-Shan], Chien, S.Y.[Shao-Yi], Yang, M.H.[Ming-Hsuan],
Learning Discriminative Shrinkage Deep Networks for Image Deconvolution,
ECCV22(XIX:217-234).
Springer DOI 2211
BibRef

Sanders, T.[Toby],
Blind Deconvolution Using the Sure-Blur Criterion and Linear PSF Expansions,
ICIP22(3475-3479)
IEEE DOI 2211
Deconvolution, Filtering, Gaussian distribution, Minimization, Optimization, Blind deconvolution, SURE, Wiener filtering BibRef

Kotera, J.[Jan], Šroubek, F.[Filip], Šmidl, V.[Václav],
Improving Neural Blind Deconvolution,
ICIP21(1954-1958)
IEEE DOI 2201
Learning systems, Deconvolution, Neural networks, Image restoration, Convolutional neural networks, Convergence, multiscale BibRef

Hu, X.[Xiaowan], Ma, R.[Ruijun], Liu, Z.H.[Zhi-Hong], Cai, Y.H.[Yuan-Hao], Zhao, X.L.[Xiao-Le], Zhang, Y.[Yulun], Wang, H.Q.[Hao-Qian],
Pseudo 3D Auto-Correlation Network for Real Image Denoising,
CVPR21(16170-16179)
IEEE DOI 2111
Deep learning, Visualization, Convolution, Stacking, Memory management, Feature extraction BibRef

Soh, J.W.[Jae Woong], Cho, N.I.[Nam Ik],
Deep Universal Blind Image Denoising,
ICPR21(747-754)
IEEE DOI 2105
Noise reduction, Tools, Random variables, Bayes methods, Pattern recognition BibRef

Ko, H.C.[Hung-Chih], Chang, J.Y.[Je-Yuan], Ding, J.J.[Jian-Jiun],
Deep Priors Inside an Unrolled and Adaptive Deconvolution Model,
ACCV20(II:371-388).
Springer DOI 2103
BibRef

Unni, V.S., Chaudhury, K.N.,
Kernel Regularization for Image Restoration,
ICIP20(943-947)
IEEE DOI 2011
Image restoration, Kernel, Eigenvalues and eigenfunctions, Noise reduction, Image resolution, Convex functions, Deconvolution, kernel denoiser BibRef

Ren, D., Zhang, K., Wang, Q., Hu, Q., Zuo, W.,
Neural Blind Deconvolution Using Deep Priors,
CVPR20(3338-3347)
IEEE DOI 2008
Kernel, Deconvolution, Optimization, Electronics packaging, Machine learning, Estimation, Convolution BibRef

Zhao, H., Shao, W., Bao, B., Li, H.,
A Simple and Robust Deep Convolutional Approach to Blind Image Denoising,
CLI19(3943-3951)
IEEE DOI 2004
Code, Convolutional Networks.
WWW Link. AWGN, convolutional neural nets, feature extraction, Gaussian noise, image denoising, noise estimation BibRef

Wang, Z., Wang, Z., Li, Q., Bilen, H.,
Image Deconvolution with Deep Image and Kernel Priors,
RLQ19(980-989)
IEEE DOI 2004
deconvolution, image reconstruction, image restoration, inverse problems, learning (artificial intelligence), Learning Free BibRef

Aljadaany, R.[Raied], Pal, D.K.[Dipan K.], Savvides, M.[Marios],
Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution,
CVPR19(10227-10236).
IEEE DOI 2002
BibRef

Guo, S.[Shi], Yan, Z.[Zifei], Zhang, K.[Kai], Zuo, W.M.[Wang-Meng], Zhang, L.[Lei],
Toward Convolutional Blind Denoising of Real Photographs,
CVPR19(1712-1722).
IEEE DOI 2002
BibRef

Kang, D., Yoo, S.I.,
Multi-Image Blind Deconvolution Using Low-Rank Representation,
ICIP19(4669-4673)
IEEE DOI 1910
BibRef

Yao, L.S., Ren, D., Yin, Q.,
Understanding Kernel Size in Blind Deconvolution,
WACV19(2068-2076)
IEEE DOI 1904
deconvolution, image restoration, optimisation, blind deconvolution methods, support domain, BibRef

Anger, J., Facciolo, G., Delbracio, M.,
Modeling Realistic Degradations in Non-Blind Deconvolution,
ICIP18(978-982)
IEEE DOI 1809
Quantization (signal), Deconvolution, Degradation, Image restoration, Cameras, Kernel, Stochastic processes, gamma correction BibRef

Lin, Y.Z.[Yun-Zhi], Shao, W.Z.[Wen-Ze],
Robust Blind Deconvolution Using Relative Total Variation as a Regularization Penalty,
PSIVTWS17(325-337).
Springer DOI 1806
BibRef

Meinhardt, T., Moeller, M., Hazirbas, C., Cremers, D.,
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems,
ICCV17(1799-1808)
IEEE DOI 1802
deconvolution, image denoising, image restoration, image segmentation, inverse problems, Training BibRef

Shaham, T.R.[Tamar Rott], Michaeli, T.[Tomer],
Deformation Aware Image Compression,
CVPR18(2453-2462)
IEEE DOI 1812
Image coding, Strain, Transform coding, Codecs, Measurement uncertainty, Visualization, Distortion measurement BibRef

Blau, Y., Michaeli, T.,
The Perception-Distortion Tradeoff,
CVPR18(6228-6237)
IEEE DOI 1812
Distortion, Distortion measurement, Image restoration, Image resolution, Visualization, Indexes BibRef

Shaham, T.R.[Tamar Rott], Michaeli, T.[Tomer],
Visualizing Image Priors,
ECCV16(VI: 136-153).
Springer DOI 1611
BibRef

He, F.Y.[Fu-Yun], Zhang, Z.S.[Zhi-Sheng],
Bayesian image blind restoration based on differential evolution optimization,
ICIVC16(15-18)
IEEE DOI 1610
Bayes methods BibRef

Fujisawa, T., Ikehara, M.,
Blind image deconvolution using specified HPF for feature extraction and conjugate gradient method in frequency domain,
ICIP16(2713-2717)
IEEE DOI 1610
Convolution BibRef

Aouinti, F., Nasri, M., Moussaoui, M., Benchaou, S., Zinedine, K.,
Satellite Image Restoration by Applying the Genetic Approach to the Wiener Deconvolution,
CGiV16(57-61)
IEEE DOI 1608
deconvolution BibRef