5.3.10.7.1 Noise Models, Noise Level

Chapter Contents (Back)
Noise Level.

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., Süsstrunk, S.,
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

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


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

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

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
Motion Coding Evaluation, Video Quality, Video Image Quality Evaluations .


Last update:Jun 29, 2020 at 10:24:28