5.3.9.5 Multiplicative Noise Removal

Javidi, B., Wang, J.,
Optimum Filter for Detecting a Target in Multiplicative Noise and Additive Noise,
JOSA-A(14), No. 4, April 1997, pp. 836-844. 9704
BibRef

Farbiz, F.[Farzam], Menhaj, M.B.[Mohammad Bagher], Motamedi, S.A.[Seyed Ahmad], Hagan, M.T.,
A New Fuzzy Logic Filter for Image Enhancement,
SMC-B(30), No. 1, February 2000, pp. 110-120.
IEEE Top Reference. 0004
BibRef

Farbiz, F.[Farzam], Menhaj, M.B.[Mohammad Bagher], Motamedi, S.A.[Seyed Ahmad],
A Modified Iterative Fuzzy Control Based Filter for Image Enhancement with Multiplicative Noise Removal Property,
ICIP99(I:539-544).
IEEE DOI BibRef 9900
Earlier:
Fixed point filter design for image enhancement using fuzzy logic,
ICIP98(II: 838-842).
IEEE DOI 9810
BibRef

Rangayyan, R.M., Das, A.,
Filtering Multiplicative Noise in Images Using Adaptive Region Based Statistics,
JEI(7), No. 1, January 1998, pp. 222-230. 9807
BibRef

Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano], Borri, G.,
Pyramid-Based Multiresolution Adaptive Filters for Additive and Multiplicative Image Noise,
CirSysSignal(45), No. 8, August 1998, pp. 1092-1097. 9809
BibRef

Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano],
Multiresolution Local-Statistics Speckle Filtering Based on a Ratio Laplacian Pyramid,
GeoRS(36), No. 5, September 1998, pp. 1466.
IEEE Top Reference. BibRef 9809
Earlier:
Multiresolution Adaptive Filtering of Signal-Dependent Noise Based on a Generalized Laplacian Pyramid,
ICIP97(I: 381-384).
IEEE DOI BibRef

Alparone, L.[Luciano], Baronti, S.[Stefano], Aiazzi, B.[Bruno], Garzelli, A.,
Spatial Methods for Multispectral Pansharpening: Multiresolution Analysis Demystified,
GeoRS(54), No. 5, May 2016, pp. 2563-2576.
IEEE DOI 1604
Laplace equations BibRef

Hawwar, Y., Reza, A.,
Spatially adaptive multiplicative noise image denoising technique,
IP(11), No. 12, December 2002, pp. 1397-1404.
IEEE DOI 0301
BibRef

Huang, L.L.[Li-Li], Xiao, L.[Liang], Wei, Z.H.[Zhi-Hui],
Multiplicative Noise Removal via a Novel Variational Model,
JIVP(2010), No. 2010, pp. xx-yy.
DOI Link 1003
BibRef

Zhang, J.[Jun], Wei, Z.H.[Zhi-Hui], Xiao, L.[Liang],
Adaptive Fractional-order Multi-scale Method for Image Denoising,
JMIV(43), No. 1, May 2012, pp. 39-49.
WWW Link. 1204
BibRef

Aja-Fernandez, S.[Santiago], Vegas-Sanchez-Ferrero, G.[Gonzalo], Martin-Fernandez, M.[Marcos], Alberola-Lopez, C.[Carlos],
Automatic noise estimation in images using local statistics. Additive and multiplicative cases,
IVC(27), No. 6, 4 May 2009, pp. 756-770.
Elsevier DOI 0904
Noise estimation; Mode; Restoration; Gaussian noise; Local statistics BibRef

Steidl, G., Teuber, T.,
Removing Multiplicative Noise by Douglas-Rachford Splitting Methods,
JMIV(36), No. 2, February 2010, pp. xx-yy.
Springer DOI 1002
BibRef

Setzer, S.[Simon], Steidl, G., Teuber, T.,
Deblurring Poissonian images by split Bregman techniques,
JVCIR(21), No. 3, April 2010, pp. 193-199.
Elsevier DOI 1003
Deblurring; Poisson noise; I-divergence; Kullback-Leibler divergence; TV; Alternating split Bregman algorithm; Douglas-Rachford splitting BibRef

Bioucas-Dias, J.M., Figueiredo, M.A.T.,
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization,
IP(19), No. 7, July 2010, pp. 1720-1730.
IEEE DOI 1007
BibRef

Afonso, M.V., Bioucas-Dias, J.M., Figueiredo, M.A.T.,
Fast Image Recovery Using Variable Splitting and Constrained Optimization,
IP(19), No. 9, September 2010, pp. 2345-2356.
IEEE DOI 1008
BibRef

Teodoro, A.M., Bioucas-Dias, J.M., Figueiredo, M.A.T.,
A Convergent Image Fusion Algorithm Using Scene-Adapted Gaussian-Mixture-Based Denoising,
IP(28), No. 1, January 2019, pp. 451-463.
IEEE DOI 1810
BibRef
Earlier:
Image restoration and reconstruction using variable splitting and class-adapted image priors,
ICIP16(3518-3522)
IEEE DOI 1610
Convex functions, Noise reduction, Convergence, Noise measurement, Image fusion, Linear programming, Inverse problems, Plug-and-play. Gaussian mixture model BibRef

Afonso, M.V., Bioucas-Dias, J.M.[Jose M.], Figueiredo, M.A.T.[Mario A. T.],
An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems,
IP(20), No. 3, March 2011, pp. 681-695.
IEEE DOI 1103
BibRef

Figueiredo, M.A.T.[Mario A. T.], Bioucas-Dias, J.M.[Jose M.],
Restoration of Poissonian Images Using Alternating Direction Optimization,
IP(19), No. 12, December 2010, pp. 3133-3145.
IEEE DOI 1011
BibRef
And:
Frame-based deconvolution of Poissonian images using alternating direction optimization,
ICIP10(3549-3552).
IEEE DOI 1009
BibRef

Rodrigues, I.[Isabel], Sanches, J.M.[Joao M.],
Fluorescence microscopy imaging denoising with log-Euclidean priors and photobleaching compensation,
ICIP09(809-812).
IEEE DOI 0911
BibRef

Rodrigues, I.[Isabel], Sanches, J.M.[Joao M.], Bioucas-Dias, J.M.[Jose M.],
Denoising of medical images corrupted by Poisson noise,
ICIP08(1756-1759).
IEEE DOI 0810

See also Medical Image Noise Reduction Using the Sylvester-Lyapunov Equation. BibRef

Li, F.[Fang], Ng, M.K.[Michael K.], Shen, C.M.[Chao-Min],
Multiplicative Noise Removal With Spatially Varying Regularization Parameters,
SIIMS(3), No. 1, 2010, pp. 1-20.
DOI Link 1002
multiplicative noise; total variation; textures; spatially varying regularization parameters BibRef

Fang, F.M.[Fa-Ming], Li, F.[Fang], Yang, X.M.[Xiao-Mei], Shen, C.M.[Chao-Min], Zhang, G.X.[Gui-Xu],
Single image dehazing and denoising with variational method,
IASP10(219-222).
IEEE DOI 1004
BibRef

Shi, J.N.[Jia-Ning], Osher, S.J.[Stanley J.],
A Nonlinear Inverse Scale Space Method For A Convex Multiplicative Noise Model,
SIIMS(1), No. 3, 2008, pp. 294-321. inverse scale space; total variation; multiplicative noise; denoising; Bregman distance
DOI Link BibRef 0800

Durand, S.[Sylvain], Fadili, J.[Jalal], Nikolova, M.[Mila],
Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients,
JMIV(36), No. 3, March 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients,
SSVM09(282-294).
Springer DOI 0906
BibRef

Chen, D.Q., Cheng, L.Z.,
Spatially Adapted Total Variation Model to Remove Multiplicative Noise,
IP(21), No. 4, April 2012, pp. 1650-1662.
IEEE DOI 1204
BibRef

Shi, B.[Baoli], Huang, L.H.[Li-Hong], Pang, Z.F.[Zhi-Feng],
Fast algorithm for multiplicative noise removal,
JVCIR(23), No. 1, January 2012, pp. 126-133.
Elsevier DOI 1112
Multiplicative noise; Anisotropic total variation; Maximum a posteriori; Convex function; Alternating minimization algorithm; Proximal operator; Gamma distribution; Newton method BibRef

Yun, S., Woo, H.,
A New Multiplicative Denoising Variational Model Based on m th Root Transformation,
IP(21), No. 5, May 2012, pp. 2523-2533.
IEEE DOI 1204
BibRef

Chan, R.H., Ma, J.,
A Multiplicative Iterative Algorithm for Box-Constrained Penalized Likelihood Image Restoration,
IP(21), No. 7, July 2012, pp. 3168-3181.
IEEE DOI 1206
BibRef

Huang, Y.M., Moisan, L., Ng, M.K., Zeng, T.,
Multiplicative Noise Removal via a Learned Dictionary,
IP(21), No. 11, November 2012, pp. 4534-4543.
IEEE DOI 1210
BibRef

Xiao, Y.[Yu], Zeng, T.Y.[Tie-Yong],
Poisson noise removal via learned dictionary,
ICIP10(1177-1180).
IEEE DOI 1009
BibRef

Liu, J.[Jun], Huang, T.Z.[Ting-Zhu], Xu, Z.B.[Zong-Ben], Lv, X.G.[Xiao-Guang],
High-order total variation-based multiplicative noise removal with spatially adapted parameter selection,
JOSA-A(30), No. 10, October 2013, pp. 1956-1966.
DOI Link 1310
BibRef

Kang, M.J.[Myung-Joo], Yun, S.W.[Sang-Woon], Woo, H.[Hyenkyun],
Two-Level Convex Relaxed Variational Model for Multiplicative Denoising,
SIIMS(6), No. 2, 2013, pp. 875-903.
DOI Link 1307
BibRef

Dong, Y.Q., Zeng, T.Y.,
A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise,
SIIMS(6), No. 3, 2013, pp. 1598-1625.
DOI Link 1310
BibRef

Sciacchitano, F.[Federica], Dong, Y.Q.[Yi-Qiu], Zeng, T.Y.[Tie-Yong],
Variational Approach for Restoring Blurred Images with Cauchy Noise,
SIIMS(8), No. 3, 2015, pp. 1894-1922.
DOI Link 1511
BibRef

Chen, L.Y.[Li-Yuan], Zeng, T.Y.[Tie-Yong],
A Convex Variational Model for Restoring Blurred Images with Large Rician Noise,
JMIV(53), No. 1, September 2015, pp. 92-111.
WWW Link. 1505
BibRef

Hao, Y.[Yan], Xu, J.L.[Jian-Lou],
An effective dual method for multiplicative noise removal,
JVCIR(25), No. 2, 2014, pp. 306-312.
Elsevier DOI 1402
Image denoising BibRef

Wang, F., Zhao, X.L., Ng, M.K.,
Multiplicative Noise and Blur Removal by Framelet Decomposition and l_1 -Based L-Curve Method,
IP(25), No. 9, September 2016, pp. 4222-4232.
IEEE DOI 1609
convex programming BibRef

Zhao, X.L., Wang, F., Ng, M.K.,
A New Convex Optimization Model for Multiplicative Noise and Blur Removal,
SIIMS(7), No. 1, 2014, pp. 456-475.
DOI Link 1404
BibRef

Chan, R., Yang, H., Zeng, T.,
A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise,
SIIMS(7), No. 1, 2014, pp. 98-127.
DOI Link 1404
BibRef

Chen, Y.J.[Yun-Jin], Feng, W.[Wensen], Ranftl, R., Qiao, H.[Hong], Pock, T.[Thomas],
A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction,
SPLetters(21), No. 11, November 2014, pp. 1370-1374.
IEEE DOI 1408
Markov processes BibRef

Feng, W.[Wensen], Qiao, H.[Hong], Chen, Y.J.[Yun-Jin],
Poisson Noise Reduction with Higher-Order Natural Image Prior Model,
SIIMS(9), No. 3, 2016, pp. 1502-1524.
DOI Link 1610
BibRef

Feng, W.[Wensen], Chen, Y.J.[Yun-Jin],
Speckle Reduction with Trained Nonlinear Diffusion Filtering,
JMIV(58), No. 1, May 2017, pp. 162-178.
WWW Link. 1704
BibRef

Kang, M.M.[Myeong-Min], Kang, M.J.[Myung-Joo], Jung, M.Y.[Mi-Youn],
Nonconvex higher-order regularization based Rician noise removal with spatially adaptive parameters,
JVCIR(32), No. 1, 2015, pp. 180-193.
Elsevier DOI 1511
Rician noise removal BibRef

Sharif, M.[Muhammad], Hussain, A.[Ayyaz], Jaffar, M.A.[Muhammad Arfan], Choi, T.S.[Tae-Sun],
Fuzzy-based hybrid filter for Rician noise removal,
SIViP(10), No. 1, February 2016, pp. 215-224.
Springer DOI 1601
BibRef

Chen, L.X.[Li-Xia], Liu, X.J.[Xu-Jiao], Wang, X.W.[Xue-Wen], Zhu, P.F.[Ping-Fang],
Multiplicative Noise Removal via Nonlocal Similarity-Based Sparse Representation,
JMIV(54), No. 2, February 2016, pp. 199-215.
Springer DOI 1602
BibRef

Liu, M.[Min], Fan, Q.B.[Qi-Bin],
A modified convex variational model for multiplicative noise removal,
JVCIR(36), No. 1, 2016, pp. 187-198.
Elsevier DOI 1603
Multiplicative noise BibRef

Ullah, A.[Asmat], Chen, W.[Wen], Sun, H.G.[Hong-Guang], Khan, M.A.[Mushtaq Ahmad],
A modified multi-grid algorithm for a novel variational model to remove multiplicative noise,
JVCIR(40, Part B), No. 1, 2016, pp. 485-501.
Elsevier DOI 1610
Maximum a posteriori (MAP) BibRef

Escande, P.[Paul], Weiss, P.[Pierre], Zhang, W.X.[Wen-Xing],
A Variational Model for Multiplicative Structured Noise Removal,
JMIV(57), No. 1, January 2017, pp. 43-55.
Springer DOI 1701
BibRef

de los Reyes, J.C., Schönlieb, C.B., Valkonen, T.,
Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models,
JMIV(57), No. 1, January 2017, pp. 1-25.
Springer DOI 1701
BibRef

Karami, A.[Azam], Tafakori, L.[Laleh],
Image denoising using generalised Cauchy filter,
IET-IPR(11), No. 9, September 2017, pp. 767-776.
DOI Link 1709
BibRef

Xu, X.L.[Xin-Li], Yu, T.[Teng], Xu, X.M.[Xin-Mei], Hou, G.J.[Guo-Jia], Liu, R.W.[Ryan Wen], Pan, H.Z.[Hui-Zhu],
Variational total curvature model for multiplicative noise removal,
IET-CV(12), No. 4, June 2018, pp. 542-552.
DOI Link 1805
BibRef

Chen, L.X.[Li-Xia], Zhu, P.F.[Ping-Fang], Wang, X.W.[Xue-Wen],
Low-rank constraint with sparse representation for image restoration under multiplicative noise,
SIViP(13), No. 1, February 2019, pp. 179-187.
WWW Link. 1901
BibRef

Yao, W., Guo, Z., Sun, J., Wu, B., Gao, H.,
Multiplicative Noise Removal for Texture Images Based on Adaptive Anisotropic Fractional Diffusion Equations,
SIIMS(12), No. 2, 2019, pp. 839-873.
DOI Link 1907
BibRef

Ren, F.[Fuquan], Zhou, R.R.[Roberta Rui],
Optimization model for multiplicative noise and blur removal based on Gaussian curvature regularization,
JOSA-A(35), No. 5, May 2018, pp. 798-812.
DOI Link 1912
Image reconstruction-restoration, Inverse problems, Noise in imaging systems, Fourier transforms, Synthetic aperture radar BibRef

Liu, P.F.[Peng-Fei],
Hybrid higher-order total variation model for multiplicative noise removal,
IET-IPR(14), No. 5, 17 April 2020, pp. 862-873.
DOI Link 2004
BibRef

Liu, X.X.[Xiao-Xia], Lu, J.[Jian], Shen, L.X.[Li-Xin], Xu, C.[Chen], Xu, Y.[Yuesheng],
Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm,
SIIMS(13), No. 3, 2020, pp. 1595-1629.
DOI Link 2010
BibRef

Yang, H.[Huan], Li, H.W.[Hong-Wei], Duan, Y.P.[Yu-Ping],
Adaptive trainable non-linear reaction diffusion for Rician noise removal,
IET-IPR(14), No. 14, December 2020, pp. 3547-3561.
DOI Link 2012
BibRef

Liu, Z.F.[Zhi-Fang], Chang, H.[Huibin], Duan, Y.P.[Yu-Ping],
Variational Rician Noise Removal via Splitting on Spheres,
SIIMS(15), No. 2, 2022, pp. 521-549.
DOI Link 2205
BibRef

Wu, T.T.[Ting-Ting], Gu, X.Y.[Xiao-Yu], Li, Z.[Zeyu], Li, Z.[Zhi], Niu, J.W.[Jian-Wei], Zeng, T.Y.[Tie-Yong],
Efficient Boosted DC Algorithm for Nonconvex Image Restoration with Rician Noise,
SIIMS(15), No. 2, 2022, pp. 424-454.
DOI Link 2205
BibRef

Seelamantula, C.S.[Chandra Sekhar], Blu, T.[Thierry],
Image denoising in multiplicative noise,
ICIP15(1528-1532)
IEEE DOI 1512
Gamma distribution BibRef

Kitchener, M.A.[Matthew Andrew], Bouzerdoum, A.[Abdesselam], Phung, S.L.[Son Lam],
Adaptive regularization for multiple image restoration using an extended Total Variations approach,
ICIP11(697-700).
IEEE DOI 1201
BibRef

Aubert, G.[Gilles], Aujol, J.F.[Jean-François],
A Nonconvex Model to Remove Multiplicative Noise,
SSVM07(68-79).
Springer DOI 0705
BibRef

Ponomarenko, N.N.[Nikolay N.], Lukin, V.V.[Vladimir V.], Astola, J.T.[Jaakko T.], Egiazarian, K.O.[Karen O.],
Non-local Sigma Filter,
CIAP15(II:483-493).
Springer DOI 1511

See also Automatic Design of Locally Adaptive Filters for Pre-processing of Images Subject to Further Interpretation. BibRef

Ponomarenko, N.N.[Nikolay N.], Lukin, V.V.[Vladimir V.], Egiazarian, K.O.[Karen O.], Astola, J.T.[Jaakko T.], Vozel, B.[Benoit], Chehdi, K.[Kacem],
Hybrid Sigma Filter for Processing Images Corrupted by Multiplicative Noise,
ACIVS06(46-54).
Springer DOI 0609
BibRef

Alamgeer, S.[Sana], Farias, M.C.Q.[Mylène C. Q.],
Light Field Image Quality Assessment with Dense Atrous Convolutions,
ICIP22(2441-2445)
IEEE DOI 2211
Image quality, Deep learning, Image coding, Convolution, Neural networks, Streaming media, Feature extraction, Light Field Images BibRef

You, J.Y.[Jun-Yong], Yan, J.[Jie],
Explore Spatial and Channel Attention in Image Quality Assessment,
ICIP22(26-30)
IEEE DOI 2211
Image quality, Visualization, Sensitivity, Codes, Spatial databases, Quality assessment, Contrast sensitivity, visual mechanism BibRef

Tliba, M.[Marouane], Sekhri, A.[Aymen], Kerkouri, M.A.[Mohamed Amine], Chetouani, A.[Aladine],
Deep-Based Quality Assessment of Medical Images Through Domain Adaptation,
ICIP22(3692-3696)
IEEE DOI 2211
Measurement, Image quality, Adaptation models, Ultrasonic imaging, Predictive models, Data models, Quality assessment, Medical images, self-attention BibRef

Sendjasni, A.[Abderrezzaq], Traparic, D.[David], Larabi, M.C.[Mohamed-Chaker],
Investigating Normalization Methods for CNN-Based Image Quality Assessment,
ICIP22(4113-4117)
IEEE DOI 2211
Training, Degradation, Image quality, Databases, Image color analysis, Robustness, Distance measurement, model performance BibRef

Jiang, W.[Wei], Li, L.[Litian], Ma, Y.[Yi], Zhai, Y.Q.[Yong-Qi], Yang, Z.[Zheng], Wang, R.G.[Rong-Gang],
Image Quality Assessment with Transformers and Multi-Metric Fusion Modules,
CLIC22(1804-1808)
IEEE DOI 2210
Measurement, Image quality, Nonlinear distortion, Superresolution, Transformers, Feature extraction, Quality assessment BibRef

Yu, L.W.[Liang-Wei], Wang, Z.[Zhao], Ye, Y.[Yan], Zhu, L.Y.[Ling-Yu], Wang, S.Q.[Shi-Qi],
A Soft-ranked Index Fusion Framework with Saliency Weighting for Image Quality Assessment,
CLIC22(1809-1813)
IEEE DOI 2210
Image quality, Visualization, Image coding, Memory, Robustness, Quality assessment BibRef

He, G.[Gang], Wang, Y.[Yong], Xu, L.[Li], Zhang, W.L.[Wen-Li], Sun, M.[Ming], Wen, X.[Xing],
Focused Feature Differentiation Network for Image Quality Assessment,
CLIC22(1799-1803)
IEEE DOI 2210
Image quality, Deep learning, Fuses, Convolution, Machine vision, Conferences, Neural networks BibRef

Estrada, D.N.D.[David Norman Díaz], Pedersen, M.[Marius],
Impact of Pooling Methods on Image Quality Metrics,
IPTA22(1-6)
IEEE DOI 2206
Measurement, Image quality, Databases, Image processing, image quality, metrics, pooling BibRef

Anikeeva, I., Chibunichev, A.,
Requirements for Aerial Images Quality, Obtained for Mapping Purposes,
ISPRS21(B2-2021: 777-784).
DOI Link 2201
BibRef

Yalcin, I., Kocaman, S., Saunier, S., Albinet, C.,
Radiometric Quality Assessment for Maxar HD Imagery,
ISPRS21(B3-2021: 797-804).
DOI Link 2201
BibRef

Bang, D.[Duhyeon], Shim, H.J.[Hyun-Jung],
MGGAN: Solving Mode Collapse Using Manifold-Guided Training,
MELEX21(2347-2356)
IEEE DOI 2112
Training, Manifolds, Image quality, Visualization, Transforms, Tools, Network architecture BibRef

Hammou, D.[Dounia], Fezza, S.A.[Sid Ahmed], Hamidouche, W.[Wassim],
EGB: Image Quality Assessment based on Ensemble of Gradient Boosting,
NTIRE21(541-549)
IEEE DOI 2109
Image quality, Measurement, Computational modeling, Tools, Boosting, Prediction algorithms, Feature extraction BibRef

Guo, Q.Y.[Qian-Yu], Wen, J.[Jing],
Multi-level Fusion Based Deep Convolutional Network for Image Quality Assessment,
MOI2QDN20(670-678).
Springer DOI 2103
BibRef

Xu, S.[Sascha], Bauer, J.[Jan], Axmann, B.[Benjamin], Maass, W.[Wolfgang],
Cd2: Combined Distances of Contrast Distributions for Image Quality Analysis,
ISVC20(II:444-457).
Springer DOI 2103
BibRef

Hao, S., Li, S.,
A Weighted Mean Absolute Error Metric for Image Quality Assessment,
VCIP20(330-333)
IEEE DOI 2102
Distortion, Image quality, Databases, Mathematical model, Image edge detection, Quality assessment, PSNR, Error map, MAE, FR-IQA, distortion significance coefficient BibRef

Gu, S.Y.[Shu-Yang], Bao, J.M.[Jian-Min], Chen, D.[Dong], Wen, F.[Fang],
GIQA: Generated Image Quality Assessment,
ECCV20(XI:369-385).
Springer DOI 2011
BibRef

Endo, K., Tanaka, M., Okutomi, M.,
Classifying Degraded Images Over Various Levels Of Degradation,
ICIP20(1691-1695)
IEEE DOI 2011
Image restoration, Transform coding, Degradation, Q-factor, Estimation, Image coding, Gaussian noise, Degraded Image, Restoration BibRef

Chiu, T., Zhao, Y., Gurari, D.,
Assessing Image Quality Issues for Real-World Problems,
CVPR20(3643-3653)
IEEE DOI 2008
Task analysis, Image quality, Visualization, Image recognition, Prediction algorithms, Cameras BibRef

Fuoli, D., Huang, Z., Danelljan, M., Timofte, R., Wang, H., Jin, L., Su, D., Liu, J., Lee, J., Kudelski, M., Bala, L., Hrybov, D., Mozejko, M., Li, M., Li, S., Pang, B., Lu, C., Li, C., He, D., Li, F., Wen, S.,
NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results,
NTIRE20(1962-1974)
IEEE DOI 2008
Video recording, Quality assessment, Generative adversarial networks, Target tracking, Training, Image coding BibRef

Ma, X., Mezghani, L., Wilber, K., Hong, H., Piramuthu, R., Naaman, M., Belongie, S.,
Understanding Image Quality and Trust in Peer-to-Peer Marketplaces,
WACV19(511-520)
IEEE DOI 1904
electronic commerce, Internet, peer-to-peer computing, retail data processing, set theory, social networking (online), Computational modeling BibRef

Pramerdorfer, C.[Christopher], Kampel, M.[Martin],
Deep Objective Image Quality Assessment,
CAIP17(II: 127-138).
Springer DOI 1708
BibRef

Ortiz-Jaramillo, B., Platisa, L., Philips, W.,
iFAS: Image Fidelity Assessment,
CCIW17(83-94).
Springer DOI 1704
BibRef

Tchendjou, G.T., Alhakim, R., Simeu, E.,
Fuzzy logic modeling for objective image quality assessment,
DASIP16(98-105)
IEEE DOI 1704
correlation methods BibRef

Wu, J., Shi, G., Zhang, M., Chen, G.,
Visual information measurement with quality assessment,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Liang, Y.D.[Yu-Dong], Wang, J.J.[Jin-Jun], Wan, X.Y.[Xing-Yu], Gong, Y.H.[Yi-Hong], Zheng, N.N.[Nan-Ning],
Image Quality Assessment Using Similar Scene as Reference,
ECCV16(V: 3-18).
Springer DOI 1611
BibRef

Saad, M., Nicholas, D., McKnight, P., Quartuccio, J., Jaladi, R., Corriveau, P.,
Subtle consumer-photo quality evaluation,
ICIP16(3778-3782)
IEEE DOI 1610
Cameras BibRef

Shi, W., Jiang, F., Zhao, D.,
Image Entropy of Primitive and visual quality assessment,
ICIP16(2087-2091)
IEEE DOI 1610
Decision support systems BibRef

Temel, D., Al Regib, G.,
ReSIFT: Reliability-weighted sift-based image quality assessment,
ICIP16(2047-2051)
IEEE DOI 1610
Correlation BibRef

Cheeseman, A.K.[Alison K.], Kowalik-Urbaniak, I.A.[Ilona A.], Vrscay, E.R.[Edward R.],
Objective Image Quality Measures of Degradation in Compressed Natural Images and their Comparison with Subjective Assessments,
ICIAR16(163-172).
Springer DOI 1608
BibRef

Lu, Y., Tu, Q., Zhao, M., Gao, R., Men, A., Yang, B.,
Gradient magnitude similarity for tone-mapped image quality assessment,
VCIP15(1-4)
IEEE DOI 1605
Brightness BibRef

Buczkowski, M., Stasinski, R.[Ryszard],
Effective coverage as a new metric for image quality assessment databases comparison,
WSSIP17(1-5)
IEEE DOI 1707
Distortion, Image quality, Measurement, Silicon, Spatial, databases BibRef

Grzywalski, T., Stasinski, R.[Ryszard],
Test of six image quality assessment methods,
WSSIP15(33-36)
IEEE DOI 1603
Internet BibRef

Pambrun, J.F.[Jean-Francois], Noumeir, R.[Rita],
Limitations of the SSIM quality metric in the context of diagnostic imaging,
ICIP15(2960-2963)
IEEE DOI 1512
SSIM BibRef

Balanov, A.[Amnon], Schwartz, A.[Arik], Moshe, Y.[Yair], Peleg, N.[Nimrod],
Image quality assessment based on DCT subband similarity,
ICIP15(2105-2109)
IEEE DOI 1512
Discrete Cosine Transform (DCT) BibRef

Guo, P.F.[Peng-Fei], Zhao, X.[Xin], Zeng, D.[Delu], Liu, H.T.[Han-Tao],
A Metric for Quantifying Image Quality Induced Saliency Variation,
ICIP21(1459-1463)
IEEE DOI 2201
Image quality, Statistical analysis, Image processing, Buildings, Benchmark testing, Distortion, Image quality assessment, saliency, visual attention BibRef

Zhang, W.[Wei], Talens-Noguera, J.V.[Juan V.], Liu, H.T.[Han-Tao],
The quest for the integration of visual saliency models in objective image quality assessment: A distraction power compensated combination strategy,
ICIP15(1250-1254)
IEEE DOI 1512
Visual saliency BibRef

Dabrowski, R., Orych, A., Jenerowicz, A., Walczykowski, P.,
Preliminary Results from the Portable Imagery Quality Assessment Test Field (PIQuAT) of UAV Imagery for Imagery Reconnaissance Purposes,
UAV-g15(111-115).
DOI Link 1512
BibRef

Dabrowski, R., Jenerowicz, A.,
Portable Imagery Quality Assessment Test Field For UAV Sensors,
UAV-g15(117-122).
DOI Link 1512
BibRef

Martinez, J.[Jorge], Pistonesi, S.[Silvina], Maciel, M.C.[María Cristina], Flesia, A.G.[Ana Georgina],
Image Fusion Quality Measure Based on a Multi-scale Approach,
ISVC16(I: 836-845).
Springer DOI 1701
BibRef

Pistonesi, S.[Silvina], Martinez, J.[Jorge], Ojeda, S.M.[Silvia María], Vallejos, R.[Ronny],
A Novel Quality Image Fusion Assessment Based on Maximum Codispersion,
CIARP15(383-390).
Springer DOI 1511
BibRef

Oskarsson, M.[Magnus],
Regularizing Image Intensity Transformations Using the Wasserstein Metric,
SCIA15(275-286).
Springer DOI 1506
discretization effects in intensity transformations of images. BibRef

Zhang, W.[Wei], Borji, A., Yang, F.Z.[Fu-Zheng], Jiang, P.[Ping], Liu, H.T.[Han-Tao],
Studying the added value of computational saliency in objective image quality assessment,
VCIP14(21-24)
IEEE DOI 1504
computer vision BibRef

Guettari, N.[Nadjib], Capelle-Laize, A.S.[Anne Sophie], Carre, P.[Philippe],
Fusion of imprecise data applied to image quality assessment,
ICIP14(521-525)
IEEE DOI 1502
Feature extraction BibRef

Islam, S.M.R., Huang, X.[Xu], Le, K.[Kim],
Novel Evaluation Index for Image Quality,
DICTA14(1-8)
IEEE DOI 1502
image denoising BibRef

Omura, H.[Hajime], Minamoto, T.[Teruya],
Image quality degradation assessment based on the dual-tree complex discrete wavelet transform for evaluating digital image watermarking,
ICWAPR16(270-275)
IEEE DOI 1611
Degradation BibRef
And:
Image Quality Assessment for Measuring the Degradation by Using the Dual-Tree Complex Discrete Wavelet Transform,
ITNG15(323-328).
IEEE DOI Information Technology - New Generations (ITNG) BibRef

Minamoto, T.[Teruya], Ohmura, H.[Hajime],
Indices for image quality degradation evaluation based on wavelet transforms,
ICWAPR14(146-152)
IEEE DOI 1402
Continuous wavelet transforms BibRef

Skurowski, P.[Przemyslaw], Janiak, M.[Mateusz],
Component Weight Tuning of SSIM Image Quality Assessment Measure,
ICCVG14(57-65).
Springer DOI 1410
BibRef

Savaux, V.[Vincent], Cormier, G.[Geoffroy], Carrault, G.[Guy], Djoko-Kouam, M.[Moïse], Laferté, J.M.[Jean-Marc], Louët, Y.[Yves], Skrzypczak, A.[Alexandre],
Picture Quality Prediction in Image Processing,
ICISP14(358-366).
Springer DOI 1406
BibRef

Liu, X.W.[Xin-Wei], Pedersen, M.[Marius], Hardeberg, J.Y.[Jon Yngve],
CID:IQ: A New Image Quality Database,
ICISP14(193-202).
Springer DOI 1406
Dataset, Image Quality. BibRef

Richter, T.[Thomas],
A global image fidelity metric: Visual distance and its properties,
ICIP13(369-373)
IEEE DOI 1402
Equations BibRef

Wang, S.G.[Shui-Gen], Deng, C.W.[Chen-Wei], Lin, W.S.[Wei-Si], Zhao, B.J.[Bao-Jun], Chen, J.[Jie],
A novel SVD-based image quality assessment metric,
ICIP13(423-426)
IEEE DOI 1402
Degradation BibRef

Petrovic, V.[Vladimir], Dimitrijevic, V.[Vladimir],
Focused pooling for objective quality estimation,
ICIP13(221-225)
IEEE DOI 1402
Data models BibRef

Pesquer, L.[Lluís], Domingo, C.[Cristina], Pons, X.[Xavier],
A Geostatistical Approach for Selecting the Highest Quality MODIS Daily Images,
IbPRIA13(608-615).
Springer DOI 1307
BibRef

Åström, F.[Freddie], Felsberg, M.[Michael], Baravdish, G.[George], Lundström, C.[Claes],
Targeted Iterative Filtering,
SSVM13(1-11).
Springer DOI 1305
assessment of image denoising BibRef

Linner, E., Strand, R.,
Comparison of restoration quality on square and hexagonal grids using normalized convolution,
ICPR12(3046-3049).
WWW Link. 1302
BibRef

Zhang, L.[Lin], Li, H.Y.[Hong-Yu],
SR-SIM: A fast and high performance IQA index based on spectral residual,
ICIP12(1473-1476).
IEEE DOI 1302
BibRef

Liu, M.[Mohan], Konya, I.[Iuliu], Nandzik, J.[Jan], Flores-Herr, N.[Nicolas], Eickeler, S.[Stefan], Ndjiki-Nya, P.[Patrick],
A new framework for automatic quality assessment of print media,
ICIP12(789-792).
IEEE DOI 1302
BibRef

Lu, W.J.[Wen-Jun], Wu, M.[Min],
Reduced-reference quality assessment for retargeted images,
ICIP12(1497-1500).
IEEE DOI 1302
BibRef

Decombas, M.[Marc], Dufaux, F.[Frederic], Renan, E.[Erwann], Pesquet-Popescu, B.[Beatrice], Capman, F.[Francois],
A new object based quality metric based on SIFT and SSIM,
ICIP12(1493-1496).
IEEE DOI 1302
BibRef

Yeh, M.C.[Mei-Chen], Cheng, Y.C.[Yu-Chen],
Relative features for photo quality assessment,
ICIP12(2861-2864).
IEEE DOI 1302
BibRef

Hsu, M.C.[Ming-Chung], Wu, G.L.[Guan-Lin], Chien, S.Y.[Shao-Yi],
Combination of SSIM and JND with content-transition classification for image quality assessment,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Yin, W.Y.[Wen-Yuan], Mei, T.[Tao], Chen, C.W.[Chang Wen],
Assessing photo quality with geo-context and crowdsourced photos,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
SEQM: Edge quality assessment based on structural pixel matching,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Abdelouahad, A.A.[Abdelkaher Ait], El Hassouni, M.[Mohammed], Cherifi, H.[Hocine], Aboutajdine, D.[Driss],
Image Quality Assessment Measure Based on Natural Image Statistics in the Tetrolet Domain,
ICISP12(451-458).
Springer DOI 1208

See also HOS-Based Image Sequence Noise Removal. BibRef

Vu, C.T.[Cuong T.], Phan, T.D.[Thien D.], Banga, P.S.[Punit S.], Chandler, D.M.[Damon M.],
On the quality assessment of enhanced images: A database, analysis, and strategies for augmenting existing methods,
Southwest12(181-184).
IEEE DOI 1205
BibRef

Behrens, A.[Alexander], Bommes, M.[Michael], Gross, S.[Sebastian], Aach, T.[Til],
Image quality assessment of endoscopic panorama images,
ICIP11(3113-3116).
IEEE DOI 1201
BibRef

Zhu, J.Z.[Jia-Zhen], Fang, Y.C.[Yu-Chun], Ji, P.J.[Peng-Jun], Abdl, M.E.[Moad-El], Dai, W.[Wang],
RRAR: A novel reduced-reference IQA algorithm for facial images,
ICIP11(3313-3316).
IEEE DOI 1201
BibRef

Bondzulic, B.P.[Boban P.], Petrovic, V.S.[Vladimir S.],
Edge-based objective evaluation of image quality,
ICIP11(3305-3308).
IEEE DOI 1201
BibRef

Luo, T.[Tao], Wang, C.[Chao], Mou, X.Q.[Xuan-Qin],
Content-based image quality assessment of natural scene image distorted by quantization,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Chen, X.L.[Xiao-Lin], Zhang, R.[Rui], Zheng, S.B.[Shi-Bao],
Image quality assessment based on local edge direction histogram,
IASP11(108-112).
IEEE DOI 1112
BibRef

Wang, X.J.[Xiao-Jun], Wang, H.[Helei], Meng, C.Z.[Cang-Zeng], Yan, S.S.[Shu-Sheng], Li, L.H.[Lian-Hua],
Hypothesis test on quality measures for synthetic aperture radar images,
IASP11(123-127).
IEEE DOI 1112
BibRef

Li, Q.[Qian], Yang, C.[Cui], Liu, H.M.[Hong-Mei], Zhang, F.F.[Fang-Fang],
Structure analysis image quality measurement,
IASP11(439-443).
IEEE DOI 1112
BibRef

Zhang, R.[Rui], Zhang, X.W.[Xiao-Wei], Gong, Z.H.[Zhi-Hui], Luo, S.[Sheng], Ji, X.G.[Xiao-Gang],
Fusion Image Quality Assessment Based on Modulation Transfer Function,
ISIDF11(1-5).
IEEE DOI 1111
BibRef

Zhang, R.[Rui], Jiang, T.[Ting], Yu, Y.Y.[Yao-Yao], Gong, H.[Hui], Dong, G.J.[Guang-Jun],
Fusion Image Quality Assessment Based on Quaternion,
ISIDF11(1-6).
IEEE DOI 1111
BibRef

Li, P.X.[Ping-Xiang], Shi, L.[Lei], Yang, J.[Jie], Lu, L.J.[Li-Jun],
Assessment of Polarimetric and Interferometric Image Quality for Chinese Domestic X-Band Airborne SAR System,
ISIDF11(1-8).
IEEE DOI 1111
BibRef

Hofbauer, H.[Heinz], Uhl, A.[Andreas],
An effective and efficient visual quality index based on local edge gradients,
EUVIP11(162-167).
IEEE DOI 1110
BibRef

Sendjasni, A.[Abderrezzaq], Larabi, M.C.[Mohamed-Chaker],
Transfer Learning from Vision Transformers or ConvNets for 360-Degree Images Quality Assessmentƒ,
ICIP22(4133-4137)
IEEE DOI 2211
Image quality, Training, Adaptation models, Transfer learning, Training data, Perceptual quality, Image quality assessment, Vision transformer BibRef

Nauge, M.[Michael], Larabi, M.C.[Mohamed-Chaker], Fernandez, C.[Christine],
Quality estimation based on interest points through hierarchical saliency maps,
EUVIP11(186-191).
IEEE DOI 1110
BibRef

Hofbauer, H., Uhl, A.,
Visual quality indices and lowquality images,
EUVIP10(171-176).
IEEE DOI 1110
BibRef

Pan, F.[Feng], Huang, J.W.[Ji-Wu],
Discriminating Computer Graphics Images and Natural Images Using Hidden Markov Tree Model,
DW10(23-28).
Springer DOI 1010
BibRef

Sai, S.V.[Sergey V.], Sai, I.S.[Ilya S.], Sorokin, N.Y.[Nikolay Y.],
A Criterion of Noisy Images Quality,
ACIVS10(I: 1-9).
Springer DOI 1012
BibRef

Gkioulekas, I.[Ioannis], Evangelopoulos, G.[Georgios], Maragos, P.[Petros],
Spatial bayesian surprise for image saliency and quality assessment,
ICIP10(1081-1084).
IEEE DOI 1009
BibRef

Hore, A.[Alain], Ziou, D.[Djemel],
Image Quality Metrics: PSNR vs. SSIM,
ICPR10(2366-2369).
IEEE DOI 1008
BibRef

Almohammad, A.[Adel], Ghinea, G.[Gheorghita],
Stego image quality and the reliability of PSNR,
IPTA10(215-220).
IEEE DOI 1007
BibRef

Geary, B.[Bobby], Grecos, C.[Christos],
Image quality assessment using a rotated Gaussian discrimination function,
CVCGI10(47-52).
IEEE DOI 1006
BibRef

Vazquez-Fernandez, E.[Esteban], Dacal-Nieto, A.[Angel], Martin, F.[Fernando], Torres-Guijarro, S.[Soledad],
Entropy of Gabor Filtering for Image Quality Assessment,
ICIAR10(I: 52-61).
Springer DOI 1006
BibRef

Rouse, D.M.[David M.], Hemami, S.S.[Sheila S.],
Natural image utility assessment using image contours,
ICIP09(2217-2220).
IEEE DOI 0911
BibRef

Asatryan, D., Egiazarian, K.O.,
Quality assessment measure based on image structural properties,
LNLA09(70-73).
IEEE DOI 0908
BibRef

Xu, Y.F.[Yan-Fang], Zhang, D.N.[Ding-Nan], Gao, N.[Ning],
A Method for Evaluation of the Font Definition Quality of eBook Readers,
CISP09(1-4).
IEEE DOI 0910
BibRef

Wang, W.[Weibao], Allebach, J.P.[Jan P.], Guo, Y.D.[Yan-Dong],
Image quality evaluation using image quality ruler and graphical model,
ICIP15(2256-2259)
IEEE DOI 1512
graphical model BibRef

Han, C.Y.[Chun-Yan], Hou, Y.[Yemao], Wang, W.J.[Wen-Jia],
Image Quality Evaluation Method Based on the Relevant Parameters,
CISP09(1-4).
IEEE DOI 0910
BibRef

Li, M.[Ming], Yang, J.[Jie],
Multivariate Statistical Analysis of Existing Image Quality Metrics Over Turbulent Images,
CISP09(1-5).
IEEE DOI 0910
BibRef

Tian, Y.F.[Ya-Fei], Qin, Y.X.[Yun-Xia], Yang, J.Y.[Jia-Yuan], Guo, A.P.[Ai-Ping],
An Approach of Image Fusion Based on General Image Quality Evaluation,
CISP09(1-4).
IEEE DOI 0910
BibRef

Liu, L.X.[Li-Xiong], Wang, Y.Q.[Yuan-Quan], Wu, Y.W.[Yu-Wei],
A Wavelet-Domain Structure Similarity for Image Quality Assessment,
CISP09(1-5).
IEEE DOI 0910
BibRef

Mansoor, A.B.[Atif Bin], Anwar, A.[Adeel],
Subjective Evaluation of Image Quality Measures for White Noise Distorted Images,
ACIVS10(I: 10-17).
Springer DOI 1012
BibRef

Mansoor, A.B.[Atif Bin], Haider, M.[Maaz], Mian, A.S.[Ajmal S.], Khan, S.A.[Shoab A.],
A Hybrid Image Quality Measure for Automatic Image Quality Assessment,
SCIA09(91-98).
Springer DOI 0906
BibRef

Shao, H.[Hang], Cao, X.[Xun], Er, G.H.[Gui-Hua],
Objective quality assessment of depth image based rendering in 3DTV system,
3DTV09(1-4).
IEEE DOI 0905
BibRef

Ma, Q.[Qi], Zhang, L.M.[Li-Ming],
Image quality assessment with visual attention,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Watanabe, K.[Keishiro], Yamagishi, K.[Kazuhisa], Okamoto, J.[Jun], Takahashi, A.[Akira],
Proposal of new QoE assessment approach for quality management of IPTV services,
ICIP08(2060-2063).
IEEE DOI 0810
BibRef

Gaubatz, M.D.[Matthew D.], Hemami, S.S.[Sheila S.],
On the nearly scale-independent rank behavior of image quality metrics,
ICIP08(701-704).
IEEE DOI 0810
BibRef

Blanchet, G.[Gwendoline], Moisan, L.[Lionel], Rouge, B.[Bernard],
Measuring the Global Phase Coherence of an image,
ICIP08(1176-1179).
IEEE DOI 0810
BibRef

Tourancheau, S.[Sylvain], Autrusseau, F.[Florent], Sazzad, Z.M.P.[Z.M. Parvez], Horita, Y.[Yuukou],
Impact of subjective dataset on the performance of image quality metrics,
ICIP08(365-368).
IEEE DOI 0810
BibRef

Dumic, E., Grgic, S., Grgic, M.,
Hidden influences on image quality when comparing interpolation methods,
WSSIP08(367-372).
IEEE DOI 0806
BibRef

Luo, Y.W.[Yi-Wen], Tang, X.[Xiaoou],
Photo and Video Quality Evaluation: Focusing on the Subject,
ECCV08(III: 386-399).
Springer DOI 0810
BibRef

Ke, Y.[Yan], Tang, X.[Xiaoou], Jing, F.[Feng],
The Design of High-Level Features for Photo Quality Assessment,
CVPR06(I: 419-426).
IEEE DOI 0606
BibRef

Munoz-Moreno, E.[Emma], Aja-Fernandez, S.[Santiago], Martin-Fernandez, M.[Marcos],
A methodology for quality assessment in tensor images,
Tensor08(1-6).
IEEE DOI 0806
BibRef

Dirik, A.E., Bayram, S., Sencar, H.T., Memon, N.,
New Features to Identify Computer Generated Images,
ICIP07(IV: 433-436).
IEEE DOI 0709
Discriminate real from computer generated images. BibRef

de Waele, S., Verberne, M.J.,
Coding Gain and Tuning for Parametrized Visual Quality Metrics,
ICIP07(VI: 461-464).
IEEE DOI 0709
BibRef

Schlaisich-Frank, I.[Isolde], Agouris, P.[Peggy],
A Dependency Matrix to Assist in the Visualization of Geospatial Image Quality,
IfromI06(xx-yy).
PDF File. 0607
BibRef

Weiss, Y.[Yair], Freeman, W.T.[William T.],
What makes a good model of natural images?,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Yao, H.X.[Hong-Xun], Huseh, M.Y.[Min-Yu], Yao, G.L.[Gui-Lin], Liu, Y.Z.[Ya-Zhou],
Image Evaluation Factors,
ICIAR05(255-262).
Springer DOI 0509
BibRef

Zhang, D.[Di], Jernigan, E.,
An Information Theoretic Criterion for Image Quality Assessment Based on Natural Scene Statistics,
ICIP06(2953-2956).
IEEE DOI 0610
BibRef

Sendashonga, M., Labeau, F.,
Low Complexity Image Quality Assessment Using Frequency Domain Transforms,
ICIP06(385-388).
IEEE DOI 0610
BibRef

Zhang, C.N.[Chu-Ne], Qiu, Z.D.[Zheng-Ding], Sun, D.M.[Dong-Mei], Wu, J.[Jie],
Euclidean Quality Assessment for Binary Images,
ICPR06(II: 300-303).
IEEE DOI 0609
BibRef

Fronthaler, H., Kollreider, K., Bigun, J.,
Automatic Image Quality Assessment with Application in Biometrics,
Biometrics06(30).
IEEE DOI 0609
BibRef

Kalenova, D., Toivanen, P.J., Bochko, V.,
Preferential Spectral Image Quality Model,
SCIA05(389-398).
Springer DOI 0506
BibRef

Menegaz, G., Zambon, R.,
Towards a Semantic-Driven Metric for Image Quality,
ICIP05(III: 1176-1179).
IEEE DOI 0512
BibRef

Lehmussola, A., Ruusuvuori, P., Yli-Harja, O.,
Exploring subjective image quality through isopreference curves,
ICIP05(I: 413-416).
IEEE DOI 0512
BibRef

Yang, C.L.[Chun-Ling], Gao, W.R.[Wen-Rui], Po, L.M.[Lai-Man],
Discrete wavelet transform-based structural similarity for image quality assessment,
ICIP08(377-380).
IEEE DOI 0810
BibRef

Chen, G.H.[Guan-Hao], Yang, C.L.[Chun-Ling], Xie, S.L.[Sheng-Li],
Gradient-Based Structural Similarity for Image Quality Assessment,
ICIP06(2929-2932).
IEEE DOI 0610
BibRef

Boman, R.[Robert],
A Theoretical Limit on the Number of Effective Pixels that can be Optically Resolved on a Non-Planar Subject,
ICCV05(I: 365-369).
IEEE DOI 0510
The theoretical limit is based only on the subject size and depth. BibRef

Hao, P.W.[Peng-Wei], Zhang, C.[Chao], Dang, A.R.[An-Rong],
Co-histogram and Image Degradation Evaluation,
ICIAR04(I: 195-203).
Springer DOI 0409
BibRef

Yu, Q.J.[Qing-Jun], Xie, S.L.[Sheng-Li],
An image quality assessment method based on fuzzy inference rules,
ICARCV04(I: 702-705).
IEEE DOI 0412
BibRef

Kdrkkdinen, I., Franti, P.,
Variable metric for binary vector quantization,
ICIP04(V: 3499-3502).
IEEE DOI 0505
BibRef

Kwon, Y.B.[Young-Bin], Park, J.[Jaehwa],
Optimum block size detection for image quality measure,
ICPR04(IV: 491-494).
IEEE DOI 0409
BibRef

Singh, M.[Maneesh], Arora, H.[Himanshu], Ahuja, N.[Narendra],
A Robust Probabilistic Estimation Framework for Parametric Image Models,
ECCV04(Vol I: 508-522).
Springer DOI 0405
BibRef

Souza, A., Cheriet, M., Naoi, S., Suen, C.Y.,
Automatic filter selection using image quality assessment,
ICDAR03(508-512).
IEEE DOI 0311
BibRef

Lin, W.S.[Wei-Si], Li, D.[Dong], Xue, P.[Ping],
Discriminative analysis of pixel difference towards picture quality prediction,
ICIP03(III: 193-196).
IEEE DOI 0312
BibRef

Perko, R.[Roland], Gruber, M.[Michael],
Comparison of Quality and Information Content of Digital and Film-Based Images,
PCV02(B: 206). 0305
BibRef

Orchard, M.,
On Modeling Location Uncertainty in Images,
ICIP01(I: 13).
IEEE DOI 0108
BibRef

de Ridder, H.,
Image Processing and the Problem of Quantifying Image Quality,
ICIP01(II: 3-6).
IEEE DOI 0108
BibRef

Janssen, T.,
Understanding Image Quality,
ICIP01(II: 7).
IEEE DOI 0108
BibRef

Kusayama, T., Hamamoto, T., Hangai, S.,
A Proposal of Objective Measure Considering Subjective Observation Areas,
ICIP01(II: 1089-1092).
IEEE DOI 0108
BibRef

Orwell, J., Greenhill, D.R., Rymel, J., Jones, G.A.,
Modelling Profiles with a Mixture of Gaussians,
ICIP00(Vol I: 280-283).
IEEE DOI 0008
BibRef

Sanubari, J.[Junibakti], Tokuda, K.[Keiichi],
Image Modeling Using Two Dimensional Exponential Systems,
ICIP99(IV:386-389).
IEEE DOI BibRef 9900

Hermiston, K.J., Booth, D.M.,
Image Quality Measurement using Integer Wavelet Transformations,
ICIP99(II:293-297).
IEEE DOI BibRef 9900
Earlier:
NIIRS and Objective Image Quality Measures,
CAIP99(385-394).
Springer DOI 9909
BibRef

Denes, L.J., Gottlieb, M., Kaminsky, B., Metes, P.,
Imaging Through Scattering Media,
DARPA98(1091-1096). BibRef 9800

Ahang, Z.[Zhong], Blum, R.S.[Rick S.],
Image Quality Estimation Using Edge Intensity Histogram and a Mixture Model,
DARPA98(1053-1058). BibRef 9800

Fleury, P.[Pascal], Reichel, J., Ebrahimi, T.,
Image Quality Prediction for Bitrate Allocation,
ICIP96(III: 339-342).
IEEE DOI BibRef 9600

Bernardini, R., Kovacevic, J.,
Designing local orthogonal bases for evaluating image quality,
ICIP96(I: 577-580).
IEEE DOI 9610
BibRef
Earlier:
Local orthogonal bases,
ICIP95(III: 580-583).
IEEE DOI 9510
BibRef

Silverstein, D.A., Farrell, J.E.,
The relationship between image fidelity and image quality,
ICIP96(I: 881-884).
IEEE DOI 9610
BibRef

de Ridder, H.,
Current issues and new techniques in visual quality assessment,
ICIP96(I: 869-872).
IEEE DOI 9610
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Quality Evaluation, Visual Quality, Quality Assessment, and Imaging Models .