Liu, X.H.[Xin-Hao],
Tanaka, M.[Masayuki],
Okutomi, M.[Masatoshi],
Single-Image Noise Level Estimation for Blind Denoising,
IP(22), No. 12, 2013, pp. 5226-5237.
IEEE DOI
1312
BibRef
Earlier:
Noise level estimation using weak textured patches of a single noisy
image,
ICIP12(665-668).
IEEE DOI
1302
computational complexity
BibRef
Amano, Y.[Yusuke],
Ohashi, G.[Gosuke],
Yoshifumi, S.[Shimodaira],
Pixel-Wise Noise Level Estimation for Images,
IEICE(E96-A), No.8, August, 2013, pp. 1821-1823.
WWW Link.
1309
BibRef
Sutour, C.[Camille],
Deledalle, C.A.[Charles-Alban],
Aujol, J.F.[Jean-François],
Estimation of the Noise Level Function Based on a Nonparametric
Detection of Homogeneous Image Regions,
SIIMS(8), No. 4, 2015, pp. 2622-2661.
DOI Link
1601
BibRef
Jiang, P.[Ping],
Zhang, J.Z.[Jian-Zhou],
Fast and reliable noise level estimation based on local statistic,
PRL(78), No. 1, 2016, pp. 8-13.
Elsevier DOI
1606
BibRef
Earlier:
Fast and reliable noise estimation algorithm based on statistical
hypothesis tests,
VCIP12(1-5).
IEEE DOI
1302
White Gaussian noise
BibRef
Dong, L.,
Zhou, J.,
Tang, Y.Y.,
Noise Level Estimation for Natural Images Based on Scale-Invariant
Kurtosis and Piecewise Stationarity,
IP(26), No. 2, February 2017, pp. 1017-1030.
IEEE DOI
1702
Gaussian noise
BibRef
Dong, L.,
Zhou, J.,
Tang, Y.Y.,
Effective and Fast Estimation for Image Sensor Noise Via Constrained
Weighted Least Squares,
IP(27), No. 6, June 2018, pp. 2715-2730.
IEEE DOI
1804
AWGN, Gaussian processes, image denoising, image sensors,
image texture, least squares approximations,
weighted least squares
BibRef
Zhu, F.Y.[Feng-Yuan],
Chen, G.Y.[Guang-Yong],
Hao, J.Y.[Jian-Ye],
Heng, P.A.[Pheng-Ann],
Blind Image Denoising via Dependent Dirichlet Process Tree,
PAMI(39), No. 8, August 2017, pp. 1518-1531.
IEEE DOI
1707
BibRef
Earlier: A1, A2, A4, Only:
From Noise Modeling to Blind Image Denoising,
CVPR16(420-429)
IEEE DOI
1612
BibRef
Earlier: A2, A1, A4, Only:
An Efficient Statistical Method for Image Noise Level Estimation,
ICCV15(477-485)
IEEE DOI
1602
Bayes methods, Data models, Gaussian distribution, Image denoising,
Mixture models, Noise measurement, Noise reduction,
Bayesian nonparametrics, Image denoising,
dependent Dirichlet process, noise modeling, patch modeling,
variational inference.
Covariance matrices
BibRef
Xu, S.,
Zeng, X.,
Jiang, Y.,
Tang, Y.,
A Multiple Image-Based Noise Level Estimation Algorithm,
SPLetters(24), No. 11, November 2017, pp. 1701-1705.
IEEE DOI
1710
Databases, Estimation, Feature extraction, Image resolution,
Noise level, Noise measurement,
Computational efficiency, image denoising,
local means estimation, multiple image-based approach,
noise level estimation (NLE), noise, level-aware, feature, vector
BibRef
Khmag, A.[Asem],
Ramli, A.R.[Abd Rahman],
Al-Haddad, S.A.R.,
Kamarudin, N.[Noraziahtulhidayu],
Natural image noise level estimation based on local statistics for
blind noise reduction,
VC(34), No. 4, April 2018, pp. 575-587.
Springer DOI
1804
BibRef
Xu, S.,
Liu, T.,
Zhang, G.,
Tang, Y.,
A Two-Stage Noise Level Estimation Using Automatic Feature Extraction
and Mapping Model,
SPLetters(26), No. 1, January 2019, pp. 179-183.
IEEE DOI
1901
convolution, feature extraction, feedforward neural nets,
optical distortion, two-stage noise level estimation algorithm,
mapping model
BibRef
Xu, S.P.[Shao-Ping],
Lin, Z.Y.[Zhen-Yu],
Zhang, G.Z.[Gui-Zhen],
Liu, T.Y.[Ting-Yun],
Yang, X.H.[Xiao-Hui],
A fast yet reliable noise level estimation algorithm using shallow
CNN-based noise separator and BP network,
SIViP(14), No. 4, June 2020, pp. 763-770.
Springer DOI
2005
BibRef
El Helou, M.[Majed],
Süsstrunk, S.[Sabine],
Blind Universal Bayesian Image Denoising With Gaussian Noise Level
Learning,
IP(29), 2020, pp. 4885-4897.
IEEE DOI
2003
Noise reduction, Noise level, Training, Gaussian noise,
Image denoising, Additives, Task analysis,
CNN image denoiser optimality
BibRef
El Helou, M.[Majed],
Süsstrunk, S.[Sabine],
BIGPrior: Toward Decoupling Learned Prior Hallucination and Data
Fidelity in Image Restoration,
IP(31), 2022, pp. 1628-1640.
IEEE DOI
2202
Image restoration, Task analysis, Deep learning, Neural networks,
Noise reduction, Measurement, Degradation, Deep image restoration,
learned prior
BibRef
Lin, X.Y.[Xiao-Yu],
Bhattacharjee, D.[Deblina],
El Helou, M.[Majed],
Süsstrunk, S.[Sabine],
Fidelity Estimation Improves Noisy-Image Classification With
Pretrained Networks,
SPLetters(28), 2021, pp. 1719-1723.
IEEE DOI
2109
Feature extraction, Image restoration, Noise measurement,
Degradation, Noise level, Deep learning, Data mining, Data Fidelity
BibRef
Ma, X.Q.[Xiao-Qi],
Lin, X.Y.[Xiao-Yu],
El Helou, M.[Majed],
Süsstrunk, S.[Sabine],
Deep Gaussian Denoiser Epistemic Uncertainty and Decoupled
Dual-Attention Fusion,
ICIP21(1629-1633)
IEEE DOI
2201
Uncertainty, Frequency-domain analysis, Noise reduction,
Image restoration, Task analysis, Noise level,
neural attention
BibRef
Préaux, Y.,
Boudraa, A.,
Statistical Behavior of Teager-Kaiser Energy Operator in Presence of
White Gaussian Noise,
SPLetters(27), 2020, pp. 635-639.
IEEE DOI
2005
Noise measurement, Probability density function, Oscillators,
Gaussian noise, Standards, Gaussian distribution,
statistical moments
BibRef
Yue, H.J.[Huan-Jing],
Jiang, Z.Y.[Zhong-Yu],
Zhou, S.D.[Sheng-Di],
Yang, J.Y.[Jing-Yu],
Hou, Y.H.[Yong-Hong],
Hou, C.P.[Chun-Ping],
Deep noise estimation and removal for real-world noisy images,
SP:IC(94), 2021, pp. 116231.
Elsevier DOI
2104
Noise estimation, Noise removal, Realistic noise, Bayer pattern
BibRef
Yue, H.J.[Huan-Jing],
Zhou, S.D.[Sheng-Di],
Yang, J.Y.[Jing-Yu],
Sun, X.Y.[Xiao-Yan],
Hou, C.P.[Chun-Ping],
Deep Joint Noise Estimation and Removal for High ISO JPEG Images,
ICPR18(153-158)
IEEE DOI
1812
Estimation, ISO, Noise reduction, Noise measurement, Training,
Gaussian noise, Noise level
BibRef
Scarciglia, A.[Andrea],
Gini, F.[Fulvio],
Catrambone, V.[Vincenzo],
Bonanno, C.[Claudio],
Valenza, G.[Gaetano],
Estimation of Dynamical Noise Power in Unknown Systems,
SPLetters(30), 2023, pp. 234-238.
IEEE DOI
2303
Estimation, Time series analysis, Entropy, Random variables,
Dynamical systems, Standards, Noise measurement, Noise,
approximate entropy
BibRef
Shikkenawis, G.[Gitam],
Mitra, S.K.[Suman K.],
Saxena, A.[Ashutosh],
Noise level estimation using locality preserving natural image
statistics,
PR(151), 2024, pp. 110393.
Elsevier DOI
2404
Additive White Gaussian Noise, Noise level estimation,
2D Orthogonal Locality Preserving Discriminant Projection,
Natural image statistics
BibRef
Yesilyurt, A.B.,
Erol, A.,
Kamisli, F.,
Alatan, A.A.,
Single Image Noise Level Estimation Using Dark Channel Prior,
ICIP19(2065-2069)
IEEE DOI
1910
Noise estimation, dark channel prior,
minimum of Gaussian variables, maximum likelihood estimation
BibRef
Gupta, P.,
Bampis, C.G.,
Jin, Y.,
Bovik, A.C.,
Natural Scene Statistics for Noise Estimation,
Southwest18(85-88)
IEEE DOI
1809
Estimation, Discrete cosine transforms, Noise level, Databases, AWGN,
GSM, Standards, scale invariance, normalized bandpass responses,
noise estimation
BibRef
Yang, J.Y.[Jing-Yu],
Liu, X.[Xin],
Song, X.L.[Xiao-Lin],
Li, K.[Kun],
Estimation of Signal-Dependent Noise Level Function Using
Multi-Column Convolutional Neural Network,
ICIP17(2418-2422)
IEEE DOI
1803
Bayes methods, Convolutional neural networks, Estimation, Kernel,
Noise level, Noise measurement, Training, Noise estimation,
signal-dependent noise
BibRef
Pomenkova, J.,
Klejmova, E.,
Malach, T.,
Evaluation of background noise for significance level identification,
WSSIP17(1-5)
IEEE DOI
1707
Continuous wavelet transforms, Image processing, Testing,
Time series analysis, Time-frequency analysis, Background noise,
Significance testing, Singular value decomposition,
Time-frequency, analysis
BibRef
Turajlic, E.,
Škaljo, N.,
Begovic, A.,
A block-based noise level estimation from X-ray images in SVD domain,
WSSIP17(1-5)
IEEE DOI
1707
Algorithm design and analysis, Estimation, Image segmentation,
Noise level, Noise measurement, X-ray imaging,
Additive white Gaussian noise, Block-based methods,
Noise estimation, Singular, value, decomposition
BibRef
Huang, X.T.[Xiao-Tong],
Chen, L.[Li],
Tian, J.[Jing],
Path vs. destination: A case study of blind noise assessment using
modified ant shortest path,
ICIP15(4170-4174)
IEEE DOI
1512
Blind noisy assessment
BibRef
Kou, T.T.[Ting-Ting],
Yang, L.[Lei],
Wan, Y.[Yi],
Accurate image noise level estimation by high order polynomial local
surface approximation and statistical inference,
VCIP14(362-365)
IEEE DOI
1504
image denoising
BibRef
Shih, Y.C.[Yi-Chang],
Kwatra, V.[Vivek],
Chinen, T.[Troy],
Fang, H.[Hui],
Ioffe, S.[Sergey],
Joint Noise Level Estimation from Personal Photo Collections,
ICCV13(2896-2903)
IEEE DOI
1403
Photo collections; image noise estimation and denoising
BibRef
Tomaszewska, A.[Anna],
Blind Noise Level Detection,
ICIAR12(I: 107-114).
Springer DOI
1206
BibRef
Bosco, A.,
Bruna, A.R.,
Smith, S.,
Tomaselli, V.,
Fast Noise Level Estimation using a Convergent Multiframe Approach,
ICIP06(2621-2624).
IEEE DOI
0610
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Video Quality, Video Image Quality Evaluations .