5.3.12 Block Matching 3-D Denoising, BM3D

Chapter Contents (Back)
Restoration. BM3D.
See also BM3D Frames and Variational Image Deblurring.

Dabov, K.[Kostadin], Foi, A.[Alessandro], Katkovnik, V.[Vladimir], Egiazarian, K.O.[Karen O.],
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,
IP(16), No. 8, August 2007, pp. 2080-2095.
IEEE DOI 0709
BibRef
And:
Color Image Denoising via Sparse 3D Collaborative Filtering with Grouping Constraint in Luminance-Chrominance Space,
ICIP07(I: 313-316).
IEEE DOI 0709

See also Comments on Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering. BibRef

Dabov, K.[Kostadin], Foi, A.[Alessandro], Egiazarian, K.O.[Karen O.],
Video denoising by sparse 3D transform-domain collaborative filtering,
EUSIPCO07VBM3D. Extends the image denoising to video. BibRef 0700

Mäkinen, Y.[Ymir], Azzari, L.[Lucio], Foi, A.[Alessandro],
Collaborative Filtering of Correlated Noise: Exact Transform-Domain Variance for Improved Shrinkage and Patch Matching,
IP(29), 2020, pp. 8339-8354.
IEEE DOI 2008
BibRef
Earlier:
Exact Transform-Domain Noise Variance for Collaborative Filtering of Stationary Correlated Noise,
ICIP19(185-189)
IEEE DOI 1910
Transforms, Noise reduction, Collaboration, Kernel, Correlation, BM3D. Image denoising, correlated noise, collaborative filtering, noise power spectrum. BibRef

Lebrun, M.[Marc],
An Analysis and Implementation of the BM3D Image Denoising Method, Image Processing,
IPOL(2012), No. 2012, pp. xx-yy.
DOI Link 1210
Code, Denoising.
See also Small Neural Networks can Denoise Image Textures Well: A Useful Complement to BM3D. BibRef

Li, Y.[Ying_Jiang], Zhang, J.W.[Jiang-Wei], Wang, M.N.[Mao-Ning],
Improved BM3D denoising method,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1197-1204.
DOI Link 1712
Block matching 3D denoising. BibRef

Wang, Y.Q.[Yi-Qing],
A Note on the Size of Denoising Neural Networks,
SIIMS(9), No. 1, 2016, pp. 275-286.
DOI Link 1604
BibRef

Wang, Y.Q.[Yi-Qing], Morel, J.M.[Jean-Michel],
Can a Single Image Denoising Neural Network Handle All Levels of Gaussian Noise?,
SPLetters(21), No. 9, Sept 2014, pp. 1150-1153.
IEEE DOI 1406

See also SURE Guided Gaussian Mixture Image Denoising. Gaussian noise BibRef

Wang, Y.Q.[Yi-Qing],
Small Neural Networks can Denoise Image Textures Well: A Useful Complement to BM3D,
IPOL(6), 2016, pp. 1-7.
DOI Link 1601

See also Image denoising: Can plain neural networks compete with BM3D?.
See also Analysis and Implementation of the BM3D Image Denoising Method, Image Processing, An.
See also Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing, A. BibRef

Djurovic, I.[Igor],
Combination of the adaptive Kuwahara and BM3D filters for filtering mixed Gaussian and impulsive noise,
SIViP(11), No. 4, May 2017, pp. 753-760.
WWW Link. 1704
BibRef

Yang, D., Sun, J.,
BM3D-Net: A Convolutional Neural Network for Transform-Domain Collaborative Filtering,
SPLetters(25), No. 1, January 2018, pp. 55-59.
IEEE DOI 1801
collaborative filtering, feedforward neural nets, grey systems, image colour analysis, image denoising, image matching, nonlocal methods BibRef

Tibbs, A.B.[Alexander B.], Daly, I.M.[Ilse M.], Roberts, N.W.[Nicholas W.], Bull, D.R.[David R.],
Denoising imaging polarimetry by adapted BM3D method,
JOSA-A(35), No. 4, April 2018, pp. 690-701.
DOI Link 1804
Image reconstruction-restoration, Polarimetry BibRef

Balaji, L., Thyagharajan, K.K.,
An enhanced performance for H.265/SHVC based on combined AEGBM3D filter and back-propagation neural network,
SIViP(12), No. 5, July 2018, pp. 809-817.
WWW Link. 1806
BibRef

Feng, Q.P.[Qin-Ping], Tao, S.P.[Shu-Ping], Xu, C.[Chao], Jin, G.[Guang],
BM3D-GT&AD: an improved BM3D denoising algorithm based on Gaussian threshold and angular distance,
IET-IPR(14), No. 3, 28 February 2020, pp. 431-441.
DOI Link 2002
BibRef

Ehret, T.[Thibaud], Arias, P.[Pablo],
Implementation of VBM3D and Some Variants,
IPOL(11), 2021, pp. 374-395.
DOI Link 2112
Code, Viedo Denoise. VBM3D is an extension to video of the well-known image denoising algorithm BMD3.
See also Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering. o BibRef

Guo, Y.[Yu], Davy, A.[Axel], Facciolo, G.[Gabriele], Morel, J.M.[Jean-Michel], Jin, Q.Y.[Qi-Yu],
Fast, Nonlocal and Neural: A Lightweight High Quality Solution to Image Denoising,
SPLetters(28), 2021, pp. 1515-1519.
IEEE DOI 2108
Noise reduction, Image restoration, Signal processing algorithms, Training, Mobile handsets, Neural networks, Convolution, BM3D, nonlocal methods BibRef


Malik, J.[Junaid], Kiranyaz, S.[Serkan], Yamac, M.[Mehmet], Gabbouj, M.[Moncef],
BM3D VS 2-Layer ONN,
ICIP21(1994-1998)
IEEE DOI 2201
Block matching 3D denoising. AWGN, Neurons, Computational efficiency, Convolutional neural networks, Biological neural networks, discriminative learning BibRef

Hara, K., Inoue, K., Urahama, K.,
Full-Reference Metric Adaptive Image Denoising,
ICIP19(2419-2423)
IEEE DOI 1910
Denoising parameter optimization, BM3D, full-reference image quality, Kullback-Leibler divergence BibRef

Xue, F., Li, J., Blu, T.,
An Iterative Sure-Let Deconvolution Algorithm Based on BM3D Denoiser,
ICIP19(1795-1799)
IEEE DOI 1910
Image deconvolution, Stein's unbiased risk estimate (SURE), linear expansion of thresholds (LET), BM3D, finite-difference Monte-Carlo BibRef

Feng, X.C.[Xiang-Chu], Li, X.H.[Xiao-Hui], Wang, W.W.[Wei-Wei], Jia, X.X.[Xi-Xi],
Improvement of BM3D Algorithm Based on Wavelet and Directed Diffusion,
CMVIT17(28-33)
IEEE DOI 1704
Block-matching and 3D filtering. Denoising. BibRef

Metzler, C.A.[Christopher A.], Maleki, A.[Arian], Baraniuk, R.G.[Richard G.],
BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising,
ICIP16(2504-2508)
IEEE DOI 1610
BibRef
Earlier:
BM3D-AMP: A new image recovery algorithm based on BM3D denoising,
ICIP15(3116-3120)
IEEE DOI 1512
Algorithm design and analysis. Approximate Message Passing; Compressive Sensing; Denoising; Onsager BibRef

Sarjanoja, S., Boutellier, J., Hannuksela, J.,
BM3D image denoising using heterogeneous computing platforms,
DASIP15(1-8)
IEEE DOI 1605
filtering theory BibRef

Li, L.[Lin], Wang, R.G.[Rong-Gang], Wang, W.M.[Wen-Min], Gao, W.[Wen],
A low-light image enhancement method for both denoising and contrast enlarging,
ICIP15(3730-3734)
IEEE DOI 1512
BM3D; Contrast enhancement; adaptive denoising; dark channel; superpixel BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Restoration by Deconvolution, Blind Deconvolution .


Last update:Mar 16, 2024 at 20:36:19