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Earlier: A1, A2, A3, Only:
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Image quality assessment; Sparse coding; Independent component
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Code, Point Spread Function.
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Houdard, A.[Antoine],
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1202
Image quality assessment; Tchebichef moments; Similarity measure;
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Zhu, J.,
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IP(21), No. 3, March 2012, pp. 919-933.
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1203
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Grotta, S.W.,
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Tools & Toys paper.
For consumer cameras, pixel count is quantity, not quality.
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Earlier:
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IEEE DOI
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BibRef
Narwaria, M.,
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Elsevier DOI
1305
BibRef
Earlier:
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ICIP10(305-308).
IEEE DOI
1009
Biometrics; Fingerprint compression; Image Quality Metric (IQM);
Wavelets; Ridgelets; Curvelets; Wave atoms; Wavelet Scalar Quantization
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See also Iris features extraction using wave atoms.
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1611
See also Wavelets and partial differential equations for image denoising.
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Electrical impedance tomography
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1312
Image quality assessment (IQA)
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Chandler, D.M.[Damon M.],
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SPIE(Newsroom), January 15, 2014
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1402
Examining the limitations of current research into image quality
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Quality measure to take advantage of satellite data.
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1408
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Bjelopera, A.,
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WSSIP16(1-4)
IEEE DOI
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image classification
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Zhang, H.[Hang],
Ding, Y.[Yong],
Wu, P.W.[Peng Wei],
Bai, X.T.[Xue Tong],
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Nehab, D.[Diego],
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1410
Generalized sampling
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Battisti, F.[Federica],
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Objective image quality
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Cheon, M.[Manri],
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Quality of experience, Objective quality assessment,
Ambiguity interval, Viewing distance
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Devaraju, A.[Anusuriya],
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Zhao, P.P.[Pei-Pei],
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BibRef
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genetic algorithms
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IEEE DOI
1710
human visual system,
robust feature descriptors,
Distortion measurement, Gray-scale, Histograms, Image quality,
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Hanhart, P.[Philippe],
Bernardo, M.[Marco],
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Quality Assessment for Reassembled Image Files,
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IEEE DOI
1602
image processing
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Simon, L.[Loïc],
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Influence of Unknown Exterior Samples on Interpolated Values for
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1604
As size and resolution increases, where are the sources for errors in data.
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Clarkson, E.[Eric],
Barrett, H.H.[Harrison H.],
Characteristic functionals in imaging and image-quality assessment:
tutorial,
JOSA-A(33), No. 8, August 2016, pp. 1464-1475.
DOI Link
1608
Imaging systems; Image analysis; Image quality assessment
BibRef
Kuo, T.Y.[Tien-Ying],
Su, P.C.[Po-Chyi],
Tsai, C.M.[Cheng-Mou],
Improved visual information fidelity based on sensitivity
characteristics of digital images,
JVCIR(40, Part A), No. 1, 2016, pp. 76-84.
Elsevier DOI
1609
Image quality assessment
BibRef
Golestaneh, S.A.[S. Alireza],
Karam, L.J.[Lina J.],
Reduced-Reference Quality Assessment Based on the Entropy of DWT
Coefficients of Locally Weighted Gradient Magnitudes,
IP(25), No. 11, November 2016, pp. 5293-5303.
IEEE DOI
1610
BibRef
Earlier:
Reduced-reference quality assessment based on the entropy of DNT
coefficients of locally weighted gradients,
ICIP15(4117-4120)
IEEE DOI
1512
Computational modeling.
Gaussian filtering
BibRef
Golestaneh, S.A.[S. Alireza],
Karam, L.J.[Lina J.],
Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted
Transform Coefficients of Gradient Magnitudes,
CVPR17(596-605)
IEEE DOI
1711
Cameras, Discrete cosine transforms, Estimation,
Image edge detection, Kernel, Robustness
BibRef
Temel, D.,
Prabhushankar, M.,
Al Regib, G.,
UNIQUE: Unsupervised Image Quality Estimation,
SPLetters(23), No. 10, October 2016, pp. 1414-1418.
IEEE DOI
1610
decoding
BibRef
Panetta, K.A.,
Gao, C.,
Agaian, S.,
Nercessian, S.,
A New Reference-Based Edge Map Quality Measure,
SMCS(46), No. 11, November 2016, pp. 1505-1517.
IEEE DOI
1609
edge detection
BibRef
Lee, K.[Kwanghyun],
Lee, S.H.[Sang-Hoon],
A New Framework for Measuring 2D and 3D Visual Information in Terms
of Entropy,
CirSysVideo(26), No. 11, November 2016, pp. 2015-2027.
IEEE DOI
1609
Complexity theory
BibRef
Manap, R.A.,
Shao, L.,
Frangi, A.F.,
Nonparametric Quality Assessment of Natural Images,
MultMedMag(23), No. 4, October 2016, pp. 22-30.
IEEE DOI
1612
feature extraction
BibRef
Ma, K.[Kede],
Duanmu, Z.F.[Zheng-Fang],
Wu, Q.B.[Qing-Bo],
Wang, Z.[Zhou],
Yong, H.W.[Hong-Wei],
Li, H.L.[Hong-Liang],
Zhang, L.[Lei],
Waterloo Exploration Database: New Challenges for Image Quality
Assessment Models,
IP(26), No. 2, February 2017, pp. 1004-1016.
IEEE DOI
1702
BibRef
Earlier: A1, A3, A4, A2, A5, A6, A7:
Group MAD Competition? A New Methodology to Compare Objective Image
Quality Models,
CVPR16(1664-1673)
IEEE DOI
1612
image processing.
BibRef
Karimi, M.[Maryam],
Samavi, S.[Shadrokh],
Karimi, N.[Nader],
Soroushmehr, S.M.R.[S.M. Reza],
Lin, W.S.[Wei-Si],
Najarian, K.[Kayvan],
Quality assessment of retargeted images by salient region deformity
analysis,
JVCIR(43), No. 1, 2017, pp. 108-118.
Elsevier DOI
1702
Image quality assessment
BibRef
Chen, C.F.[Chao-Feng],
Mo, J.[Jiadi],
Hou, J.W.[Jing-Wen],
Wu, H.N.[Hao-Ning],
Liao, L.[Liang],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Lin, W.S.[Wei-Si],
TOPIQ: A Top-Down Approach from Semantics to Distortions for Image
Quality Assessment,
IP(33), 2024, pp. 2404-2418.
IEEE DOI Code:
WWW Link.
2404
Semantics, Feature extraction, Distortion, Image quality, Quality assessment,
Transformers, Residual neural networks, cross-scale attention
BibRef
Ding, L.,
Huang, H.,
Zang, Y.,
Image Quality Assessment Using Directional Anisotropy Structure
Measurement,
IP(26), No. 4, April 2017, pp. 1799-1809.
IEEE DOI
1704
Anisotropic magnetoresistance
BibRef
Ding, Y.[Yong],
Zhao, Y.[Yang],
Zhao, X.Y.[Xin-Yu],
Image quality assessment based on multi-feature extraction and
synthesis with support vector regression,
SP:IC(54), No. 1, 2017, pp. 81-92.
Elsevier DOI
1704
Image quality assessment
BibRef
Franks, S.[Shannon],
Neigh, C.S.R.[Christopher S. R.],
Campbell, P.K.[Petya K.],
Sun, G.Q.[Guo-Qing],
Yao, T.[Tian],
Zhang, Q.Y.[Qing-Yuan],
Huemmrich, K.F.[Karl F.],
Middleton, E.M.[Elizabeth M.],
Ungar, S.G.[Stephen G.],
Frye, S.W.[Stuart W.],
EO-1 Data Quality and Sensor Stability with Changing Orbital
Precession at the End of a 16 Year Mission,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Ding, Y.[Yong],
Zhao, X.Y.[Xin-Yu],
Zhang, Z.[Zhi],
Dai, H.[Hang],
Image Quality Assessment Based on Multi-Order Local Features
Description, Modeling and Quantification,
IEICE(E100-D), No. 6, June 2017, pp. 1303-1315.
WWW Link.
1706
BibRef
Zhan, Y.,
Zhang, R.,
Wu, Q.,
A Structural Variation Classification Model for Image Quality
Assessment,
MultMed(19), No. 8, August 2017, pp. 1837-1847.
IEEE DOI
1708
BibRef
Earlier: A1, A2, Only:
A novel structural variation detection strategy for image quality
assessment,
ICIP16(2072-2076)
IEEE DOI
1610
Acoustic distortion, Additives, Deformable models,
Distortion measurement, Image quality, Mathematical model,
Fuzzy logic, image quality assessment (IQA),
structural variation classification
BibRef
Zhou, Y.[Yu],
Li, L.[Leida],
Gu, K.[Ke],
Lu, Z.L.[Zhao-Lin],
Chen, B.[Beijing],
Tang, L.[Lu],
DIBR-Synthesized Image Quality Assessment via Statistics of Edge
Intensity and Orientation,
IEICE(E100-D), No. 8, August 2017, pp. 1929-1933.
WWW Link.
1708
BibRef
Kong, X.F.[Xiang-Fei],
Yang, Q.X.[Qing-Xiong],
No-Reference Image Quality Assessment for Image Auto-Denoising,
IJCV(126), No. 5, May 2018, pp. 537-549.
Springer DOI
1804
BibRef
Kong, X.F.[Xiang-Fei],
Li, K.[Kuan],
Yang, Q.X.[Qing-Xiong],
Liu, W.Y.[Wen-Yin],
Yang, M.H.[Ming-Hsuan],
A New Image Quality Metric for Image Auto-denoising,
ICCV13(2888-2895)
IEEE DOI
1403
BibRef
Yao, J.[Juncai],
Liu, G.Z.[Gui-Zhong],
Improved SSIM IQA of contrast distortion based on the contrast
sensitivity characteristics of HVS,
IET-IPR(12), No. 6, June 2018, pp. 872-879.
DOI Link
1805
structural similarity index metric for image quality.
BibRef
Liu, Y.H.[Yu-Hong],
Yan, H.M.[Hong-Mei],
Gao, S.B.[Shao-Bing],
Yang, K.F.[Kai-Fu],
Criteria to evaluate the fidelity of image enhancement by MSRCR,
IET-IPR(12), No. 6, June 2018, pp. 880-887.
DOI Link
1805
MSRCR: multi-scale Retinex with colour restoration
BibRef
Bai, C.[Chen],
Reibman, A.R.[Amy R.],
Image quality assessment in first-person videos,
JVCIR(54), 2018, pp. 123-132.
Elsevier DOI
1806
BibRef
Earlier:
Mutual reference frame-quality assessment for first-person videos,
ICIP17(290-294)
IEEE DOI
1803
BibRef
Earlier:
Characterizing distortions in first-person videos,
ICIP16(2440-2444)
IEEE DOI
1610
First-person videos, Local Visual Information (LVI),
Mutual reference, Image quality assessment, Pseudo-reference.
Cameras, Estimation, Partitioning algorithms,
Videos, Visualization, LVI.
near-set
BibRef
Reibman, A.R.[Amy R.],
A strategy to jointly test image quality estimators subjectively,
ICIP12(1501-1504).
IEEE DOI
1302
BibRef
Ciaramello, F.M.[Frank M.],
Reibman, A.R.[Amy R.],
Systematic stress testing of image quality estimators,
ICIP11(3101-3104).
IEEE DOI
1201
BibRef
Zhu, R.,
Zhou, F.,
Yang, W.,
Xue, J.H.,
On Hypothesis Testing for Comparing Image Quality Assessment Metrics,
SPMag(35), No. 4, July 2018, pp. 133-136.
IEEE DOI
1807
[Tips amp; Tricks]
Correlation, Gaussian distribution, Gaussian noise, Image quality,
Measurement, Testing
BibRef
Kruggel, F.,
A Simple Measure for Acuity in Medical Images,
IP(27), No. 11, November 2018, pp. 5225-5233.
IEEE DOI
1809
image enhancement, image reconstruction, image resolution,
medical image processing, image quality, medical imaging,
medical imaging
BibRef
Torkamani-Azar, F.[Farah],
Parkkinen, J.[Jussi],
Image quality assessment using block-based weighted SVD,
SIViP(12), No. 7, October 2018, pp. 1337-1344.
WWW Link.
1809
BibRef
Wang, J.H.[Ji-Heng],
Wang, S.Q.[Shi-Qi],
Wang, Z.[Zhou],
Asymmetrically Compressed Stereoscopic 3D Videos:
Quality Assessment and Rate-Distortion Performance Evaluation,
IP(26), No. 3, March 2017, pp. 1330-1343.
IEEE DOI
1703
BibRef
Earlier:
Quality prediction of asymmetrically compressed stereoscopic videos,
ICIP15(3427-3431)
IEEE DOI
1512
data compression.
3D video
BibRef
Pan, X.F.[Xiao-Fei],
Zhang, J.Q.[Jia-Qi],
Wang, S.S.[Shan-She],
Wang, S.Q.[Shi-Qi],
Zhou, Y.[Yun],
Ding, W.H.[Wen-Hua],
Yang, Y.H.[Ya-Hui],
HDR video quality assessment:
Perceptual evaluation of compressed HDR video,
JVCIR(57), 2018, pp. 76-83.
Elsevier DOI
1812
High dynamic range (HDR), Subjective quality assessment, Video compression
BibRef
Kim, D.,
Lee, S.,
Kim, C.,
Contextual Information Based Quality Assessment for Contrast-Changed
Images,
SPLetters(26), No. 1, January 2019, pp. 109-113.
IEEE DOI
1901
entropy, feature extraction, image colour analysis,
image enhancement, image processing, image representation,
2-D histogram and spatial entropy
BibRef
Zhang, C.,
Cheng, W.[Wu],
Hirakawa, K.[Keigo],
Corrupted Reference Image Quality Assessment of Denoised Images,
IP(28), No. 4, April 2019, pp. 1732-1747.
IEEE DOI
1901
BibRef
Earlier: A2, A3, Only:
Corrupted reference image quality assessment,
ICIP12(1485-1488).
IEEE DOI
1302
image denoising, image restoration,
corrupted reference image quality assessment, denoised images,
image quality assessment
BibRef
Yue, G.H.[Guang-Hui],
Hou, C.P.[Chun-Ping],
Gu, K.[Ke],
Zhou, T.W.[Tian-Wei],
Zhai, G.T.[Guang-Tao],
Combining Local and Global Measures for DIBR-Synthesized Image
Quality Evaluation,
IP(28), No. 4, April 2019, pp. 2075-2088.
IEEE DOI
1901
computational geometry, image restoration,
rendering (computer graphics), stereo image processing,
sharpness
BibRef
Gomez, L.[Luis],
Ospina, R.[Raydonal],
Frery, A.C.[Alejandro C.],
Statistical Properties of an Unassisted Image Quality Index for SAR
Imagery,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Abdoli, M.[Mohsen],
Nasiri, F.[Fatemeh],
Brault, P.[Patrice],
Ghanbari, M.[Mohammad],
Quality assessment tool for performance measurement of image contrast
enhancement methods,
IET-IPR(13), No. 5, 18 April 2019, pp. 833-842.
DOI Link
1904
BibRef
Chen, Y.J.[Yu-Jia],
Lou, Y.[Yang],
Wang, K.[Kun],
Kupinski, M.A.[Matthew A.],
Anastasio, M.A.[Mark A.],
Reconstruction-Aware Imaging System Ranking by Use of a
Sparsity-Driven Numerical Observer Enabled by Variational Bayesian
Inference,
MedImg(38), No. 5, May 2019, pp. 1251-1262.
IEEE DOI
1905
Optimization of imaging system performance should be guided by
task-based measures of image quality.
Task analysis, Reconstruction algorithms, Computational modeling,
Image reconstruction, Observers, Noise measurement,
sparse image reconstruction
BibRef
Weiss, P.[Pierre],
Escande, P.[Paul],
Bathie, G.[Gabriel],
Dong, Y.Q.[Yi-Qiu],
Contrast Invariant SNR and Isotonic Regressions,
IJCV(127), No. 8, August 2019, pp. 1144-1161.
Springer DOI
1907
Image quality measure independent of contrast changes.
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Huang, J.C.[Jui-Chan],
Huang, H.C.[Hao-Chen],
Chu, S.H.[Su-Hui],
Research on image quality in decision management system and
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JVCIR(63), 2019, pp. 102588.
Elsevier DOI
1909
Image quality, Quality model, Decision management,
Information system, Decision support system
BibRef
Cao, J.C.[Jing-Chao],
Wang, S.Q.[Shi-Qi],
Wang, R.[Ran],
Zhang, X.F.[Xin-Feng],
Kwong, S.[Sam],
Content-oriented image quality assessment with multi-label SVM
classifier,
SP:IC(78), 2019, pp. 388-397.
Elsevier DOI
1909
Image quality assessment, Image content classification,
Subjective quality, Objective quality
BibRef
Maksimovic-Moicevic, S.[Sanja],
Lukac, Ž.[Željko],
Temerinac, M.[Miodrag],
Objective estimation of subjective image quality assessment using
multi-parameter prediction,
IET-IPR(13), No. 13, November 2019, pp. 2428-2435.
DOI Link
1911
BibRef
Pérez-Ortiz, M.,
Mikhailiuk, A.,
Zerman, E.,
Hulusic, V.,
Valenzise, G.,
Mantiuk, R.K.[Rafal K.],
From Pairwise Comparisons and Rating to a Unified Quality Scale,
IP(29), 2020, pp. 1139-1151.
IEEE DOI
1911
Observers, Standards, Protocols, Quality assessment, Training,
Image quality, Probabilistic logic, Psychometric scaling,
dataset fusion
BibRef
He, S.Y.[Si-Yuan],
Liu, Z.Z.[Ze-Zheng],
Image quality assessment based on adaptive multiple Skyline query,
SP:IC(80), 2020, pp. 115676.
Elsevier DOI
1912
Image quality, Skyline, Feature fusion, Gabor wavelet
BibRef
Tran, H.T.T.[Huyen T. T.],
Hoang, T.H.[Trang H.],
Minh, P.N.[Phu N.],
Ngoc, N.P.[Nam Pham],
Thang, T.C.[Truong Cong],
A Weighted Viewport Quality Metric for Omnidirectional Images,
IEICE(E103-D), No. 1, January 2020, pp. 67-70.
WWW Link.
2001
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Yu, M.M.[Miao-Miao],
Zheng, Y.L.[Yuan-Lin],
Liao, K.Y.[Kai-Yang],
Tang, Z.S.[Zhi-Sen],
Image quality assessment via spatial-transformed domains multi-feature
fusion,
IET-IPR(14), No. 4, 27 March 2020, pp. 648-657.
DOI Link
2003
BibRef
Diamant, R.[Roee],
Shachar, I.[Ilan],
Makovsky, Y.[Yizhaq],
Ferreira, B.M.[Bruno Miguel],
Cruz, N.A.[Nuno Alexandre],
Cross-Sensor Quality Assurance for Marine Observatories,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Li, Y.J.[Ya-Jing],
Huang, B.X.[Bao-Xiang],
Yang, H.[Huan],
Hou, G.J.[Guo-Jia],
Zhang, P.F.[Peng-Fei],
Duan, J.M.[Jin-Ming],
Efficient image structural similarity quality assessment method using
image regularised feature,
IET-IPR(14), No. 16, 19 December 2020, pp. 4401-4411.
DOI Link
2103
BibRef
Yi, W.[Wei],
Wang, Y.H.[Yu-Hao],
Zeng, Y.[Yong],
Wang, Y.Q.[Ya-Qin],
Xu, J.F.[Jian-Fei],
Comprehensive Evaluation of the GF-4 Satellite Image Quality from
2015 to 2020,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Elmezayen, M.R.[Mohamed R.],
Ay, S.U.[Suat U.],
A new blind image conversion complexity metric for intelligent CMOS
image sensors,
IET-IPR(15), No. 3, 2021, pp. 683-695.
DOI Link
2106
Sensor quality.
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Sekrecka, A.[Aleksandra],
Application of the XBoost Regressor for an A Priori Prediction of UAV
Image Quality,
RS(13), No. 23, 2021, pp. xx-yy.
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2112
BibRef
Chai, X.L.[Xiong-Li],
Shao, F.[Feng],
M2OVQA: Multi-space signal characterization and multi-channel
information aggregation for quality assessment of compressed
omnidirectional videos,
JVCIR(82), 2022, pp. 103419.
Elsevier DOI
2201
Omnidirectional video quality assessment,
Image quality assessment, Compression distortion, Information aggregation
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Zhang, K.[Keke],
Fang, Y.[Ying],
Chen, W.L.[Wei-Ling],
Xu, Y.W.[Yi-Wen],
Zhao, T.S.[Tie-Song],
A Display-Independent Quality Assessment for HDR Images,
SPLetters(29), 2022, pp. 464-468.
IEEE DOI
2202
Image quality, Image coding, Task analysis, Visualization,
Signal processing algorithms, Optimized production technology,
gradient magnitude similarity (GMS)
BibRef
Sang, Q.B.[Qing-Bing],
Cao, Y.J.[Yu-Jie],
Liu, L.X.[Li-Xiong],
Hu, C.[Cong],
Wu, X.J.[Xiao-Jun],
MP2020: Visual quality assessment database for macro photography
images,
IET-IPR(16), No. 4, 2022, pp. 985-991.
DOI Link
2203
BibRef
Zhou, Y.[Yu],
Sun, Y.J.[Yan-Jing],
Li, L.D.[Lei-Da],
Gu, K.[Ke],
Fang, Y.M.[Yu-Ming],
Omnidirectional Image Quality Assessment by Distortion Discrimination
Assisted Multi-Stream Network,
CirSysVideo(32), No. 4, April 2022, pp. 1767-1777.
IEEE DOI
2204
Task analysis, Measurement, Distortion, Quality assessment, Sun,
Image coding, Visualization, Image quality assessment,
distortion discrimination
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Yan, J.B.[Jie-Bin],
Rao, J.[Jiale],
Chen, J.J.[Jun-Jie],
Tan, Z.W.[Zi-Wen],
Liu, W.[Weide],
Fang, Y.M.[Yu-Ming],
Multitask Auxiliary Network for Perceptual Quality Assessment of
Non-Uniformly Distorted Omnidirectional Images,
CirSysVideo(35), No. 3, March 2025, pp. 2782-2793.
IEEE DOI Code:
WWW Link.
2503
Distortion, Feature extraction, Adaptation models, Solid modeling,
Image quality, Visualization, Predictive models,
non-uniform distortion
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Zhang, X.F.[Xin-Feng],
Lin, W.S.[Wei-Si],
Huang, Q.M.[Qing-Ming],
Fine-Grained Image Quality Assessment: A Revisit and Further Thinking,
CirSysVideo(32), No. 5, May 2022, pp. 2746-2759.
IEEE DOI
2205
Distortion, Image coding, Databases, Image quality, Visualization,
Transform coding, Image processing, Image quality assessment,
human visual system
BibRef
Saunier, S.[Sebastien],
Karakas, G.[Gizem],
Yalcin, I.[Ilyas],
Done, F.[Fay],
Mannan, R.[Rubinder],
Albinet, C.[Clement],
Goryl, P.[Philippe],
Kocaman, S.[Sultan],
SkySat Data Quality Assessment within the EDAP Framework,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Hofbauer, H.[Heinz],
Autrusseau, F.[Florent],
Uhl, A.[Andreas],
Low Quality and Recognition of Image Content,
MultMed(24), 2022, pp. 3595-3610.
IEEE DOI
2207
Encryption, Databases, Observers, Image recognition, Cryptography,
Visualization, Distortion, Selective encryption, image recognition,
visual quality indices
BibRef
Yang, J.C.[Jia-Chen],
Yang, Y.[Yue],
Wen, J.[Jiabao],
Li, Y.[Yang],
Ercisli, S.[Sezai],
Remote Sensing Image Information Quality Evaluation via Node Entropy
for Efficient Classification,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Athar, S.[Shahrukh],
Wang, Z.[Zhou],
Degraded Reference Image Quality Assessment,
IP(32), 2023, pp. 822-837.
IEEE DOI
2301
Distortion, Image coding, Computer architecture, Pipelines,
Feature extraction, Codes, Quality assessment, image quality databases
BibRef
Rehman, A.[Abdul],
Wang, Z.[Zhou],
Reduced-reference SSIM estimation,
ICIP10(289-292).
IEEE DOI
1009
structural similarity for Image quality.
BibRef
Wang, Z.Y.[Zhe-Yin],
Shen, L.Q.[Li-Quan],
Wang, Z.Y.[Zheng-Yong],
Lin, Y.F.[Yu-Fei],
Jin, Y.L.[Yan-Liang],
Generation-Based Joint Luminance-Chrominance Learning for Underwater
Image Quality Assessment,
CirSysVideo(33), No. 3, March 2023, pp. 1123-1139.
IEEE DOI
2303
Distortion, Image color analysis, Image quality,
Feature extraction, Optical distortion, Image enhancement, Color,
sharpness distortion
BibRef
Zhu, R.[Rui],
Zhou, F.[Fei],
Yang, W.M.[Wen-Ming],
Xue, J.H.[Jing-Hao],
Statistical hypothesis testing as a novel perspective of pooling for
image quality assessment,
SP:IC(114), 2023, pp. 116942.
Elsevier DOI
2305
Image quality assessment, Pooling strategy, Hypothesis testing
BibRef
Yu, S.D.[Shao-De],
Wang, J.Y.[Jia-Yi],
Gu, J.C.[Jia-Cheng],
Jin, M.X.[Ming-Xue],
Ma, Y.L.[Yun-Ling],
Yang, L.J.[Li-Juan],
Li, J.G.[Jian-Guang],
A hybrid indicator for realistic blurred image quality assessment,
JVCIR(94), 2023, pp. 103848.
Elsevier DOI
2306
Image quality assessment, Realistic blur, Feature selection, Machine learning
BibRef
Ding, Y.Z.[Yao-Zong],
Gu, X.F.[Xing-Fa],
Liu, Y.[Yan],
Zhang, H.[Hu],
Cheng, T.H.[Tian-Hai],
Li, J.[Juan],
Wei, X.Q.[Xiang-Qin],
Gao, M.[Min],
Liang, M.[Man],
Zhang, Q.[Qian],
GF-1 WFV Surface Reflectance Quality Evaluation in Countries along
'the Belt and Road',
RS(15), No. 22, 2023, pp. 5382.
DOI Link
2311
BibRef
Zhou, W.M.[Wei-Min],
Villa, U.[Umberto],
Anastasio, M.A.[Mark A.],
Ideal Observer Computation by Use of Markov-Chain Monte Carlo With
Generative Adversarial Networks,
MedImg(42), No. 12, December 2023, pp. 3715-3724.
IEEE DOI
2312
BibRef
Tofighi, N.J.[Nafiseh Jabbari],
Elfkir, M.H.[Mohamed Hedi],
Imamoglu, N.[Nevrez],
Ozcinar, C.[Cagri],
Erdem, A.[Aykut],
Erdem, E.[Erkut],
Omnidirectional image quality assessment with local-global vision
transformers,
IVC(148), 2024, pp. 105151.
Elsevier DOI
2407
360-degree images, Image quality assessment, Vision transformers
BibRef
Fan, X.D.[Xiao-Dong],
Peng, C.[Chang],
Jiang, X.L.[Xiao-Li],
Han, Y.[Ying],
Hou, L.M.[Li-Min],
Stacked deformable convolution network with weighted non-local
attention and branch residual connection for image quality assessment,
JVCIR(103), 2024, pp. 104214.
Elsevier DOI Code:
WWW Link.
2409
Image quality assessment, Deep learning,
Deformable convolution, Self-attention
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Zhu, H.W.[Han-Wei],
Sui, X.J.[Xiang-Jie],
Chen, B.L.[Bao-Liang],
Liu, X.L.[Xue-Lin],
Chen, P.L.[Pei-Lin],
Fang, Y.M.[Yu-Ming],
Wang, S.Q.[Shi-Qi],
2AFC Prompting of Large Multimodal Models for Image Quality
Assessment,
CirSysVideo(34), No. 12, December 2024, pp. 12873-12878.
IEEE DOI Code:
WWW Link.
2501
Visualization, Distortion, Image quality,
Correlation, Accuracy, Task analysis, Large multimodal models,
two-alternative forced choice
BibRef
Gu, K.[Ke],
Liu, H.Y.[Hong-Yan],
Liu, Y.C.[Yu-Chen],
Qiao, J.F.[Jun-Fei],
Zhai, G.T.[Guang-Tao],
Zhang, W.J.[Wen-Jun],
Perceptual Information Fidelity for Quality Estimation of Industrial
Images,
CirSysVideo(35), No. 1, January 2025, pp. 477-491.
IEEE DOI
2502
Image quality, Estimation, Optical imaging, Optical distortion,
Optical noise, Brain modeling, Noise,
image content-aware adjustor
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Smith, B.C.[Brad C.],
Gatt, P.[Phil],
Resolution metric for imaging systems,
JOSA-A(42), No. 3, March 2025, pp. 378-384.
DOI Link
2503
Detector arrays, Imaging systems, Light propagation,
Matched filtering, Optical systems, Systems design
BibRef
Yan, J.B.[Jie-Bin],
Tan, Z.W.[Zi-Wen],
Fang, Y.M.[Yu-Ming],
Chen, J.J.[Jun-Jie],
Jiang, W.H.[Wen-Hui],
Wang, Z.[Zhou],
Omnidirectional Image Quality Captioning:
A Large-Scale Database and a New Model,
IP(34), 2025, pp. 1326-1339.
IEEE DOI Code:
WWW Link.
2503
Databases, Distortion, Degradation, Semantics, Image quality,
Visualization, Quality of experience, Feature extraction,
image quality caption
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Fan, H.[Hui],
Xu, L.[Lihao],
Luo, M.R.[Ming Ronnier],
Optimized principal component analysis for camera spectral
sensitivity estimation,
JOSA-A(40), No. 8, August 2023, pp. 1515-1526.
DOI Link
2503
Cameras, Distortion, Imaging systems, Multispectral imaging,
Neural networks, Spectral discrimination
BibRef
Wang, M.H.[Miao-Hui],
Xu, Z.W.[Zhuo-Wei],
Zhang, X.F.[Xiao-Fang],
Fang, Y.M.[Yu-Ming],
Lin, W.S.[Wei-Si],
Visual Quality Assessment of Composite Images: A Compression-Oriented
Database and Measurement,
IP(34), 2025, pp. 1849-1863.
IEEE DOI Code:
HTML Version.
2504
Image coding, Visualization, Distortion, Databases,
Feature extraction, Standards, Image quality, Quality of service,
compression distortion
BibRef
Wu, X.B.[Xin-Bo],
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Wu, Y.Y.[Ying-Ying],
Liu, W.[Wanan],
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Allen, S.[Stuart],
Whitaker, R.[Roger],
Liu, H.T.[Han-Tao],
Image Manipulation Quality Assessment,
CirSysVideo(35), No. 4, April 2025, pp. 3450-3461.
IEEE DOI
2504
Image quality, Databases, Computational modeling, Distortion,
Quality assessment, Visualization, Filtering algorithms, deep learning
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Wu, H.N.[Hao-Ning],
Zhu, H.W.[Han-Wei],
Zhang, Z.C.[Zi-Cheng],
Zhang, E.[Erli],
Chen, C.F.[Chao-Feng],
Liao, L.[Liang],
Li, C.Y.[Chun-Yi],
Wang, A.[Annan],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Liu, X.H.[Xiao-Hong],
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Towards Open-ended Visual Quality Comparison,
ECCV24(III: 360-377).
Springer DOI
2412
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You, Z.Y.[Zhi-Yuan],
Li, Z.[Zheyuan],
Gu, J.J.[Jin-Jin],
Yin, Z.F.[Zhen-Fei],
Xue, T.F.[Tian-Fan],
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Depicting Beyond Scores: Advancing Image Quality Assessment Through
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ECCV24(XLVII: 259-276).
Springer DOI
2412
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Catania, L.[Lorenzo],
Allegra, D.[Dario],
Redefining Visual Quality: The Impact of Loss Functions on INR-Based
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ICIP24(1973-1979)
IEEE DOI
2411
Training, Measurement, Visualization, Image coding, PSNR,
Image resolution, Crops, Image compression,
INR: Implicit neural representations
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Ge, S.W.[Song-Wei],
Mahapatra, A.[Aniruddha],
Parmar, G.[Gaurav],
Zhu, J.Y.[Jun-Yan],
Huang, J.B.[Jia-Bin],
On the Content Bias in Fréchet Video Distance,
CVPR24(7277-7288)
IEEE DOI
2410
Image quality, Sensitivity, Computational modeling,
Feature extraction, Video Generation, Evaluation
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Zhang, J.Y.[Jun-Yu],
Liu, D.[Daochang],
Park, E.[Eunbyung],
Zhang, S.C.[Shi-Chao],
Xu, C.[Chang],
Residual Learning in Diffusion Models,
CVPR24(7289-7299)
IEEE DOI
2410
Image quality, Estimation, Stochastic processes,
Differential equations, Diffusion models, Mathematical models
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Peng, F.[Fei],
Fu, H.Y.[Hui-Yuan],
Ming, A.[Anlong],
Wang, C.M.[Chuan-Ming],
Ma, H.D.[Hua-Dong],
He, S.[Shuai],
Dou, Z.[Zifei],
Chen, S.[Shu],
AIGC Image Quality Assessment via Image-Prompt Correspondence,
NTIRE24(6432-6441)
IEEE DOI Code:
WWW Link.
2410
Image quality, Visualization, Refining, Focusing, Benchmark testing,
Streaming media, Generative adversarial networks
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Li, C.Y.[Chun-Yi],
Kou, T.C.[Teng-Chuan],
Gao, Y.X.[Yi-Xuan],
Cao, Y.Q.[Yu-Qin],
Sun, W.[Wei],
Zhang, Z.C.[Zi-Cheng],
Zhou, Y.J.[Ying-Jie],
Zhang, Z.C.[Zhi-Chao],
Zhang, W.X.[Wei-Xia],
Wu, H.N.[Hao-Ning],
Liu, X.H.[Xiao-Hong],
Min, X.K.[Xiong-Kuo],
Zhai, G.T.[Guang-Tao],
AIGIQA-20K: A Large Database for AI-Generated Image Quality
Assessment,
NTIRE24(6327-6336)
IEEE DOI Code:
WWW Link.
2410
Measurement, Image quality, Image resolution, Databases,
Social networking (online), Text to image, Benchmark testing,
Image Quality Assessment
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Liu, X.H.[Xiao-Hong],
Min, X.K.[Xiong-Kuo],
Zhai, G.T.[Guang-Tao],
Li, C.Y.[Chun-Yi],
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Sun, W.[Wei],
Wu, H.N.[Hao-Ning],
Gao, Y.X.[Yi-Xuan],
Cao, Y.Q.[Yu-Qin],
Zhang, Z.C.[Zi-Cheng],
Wu, X.[Xiele],
Timofte, R.[Radu],
Peng, F.[Fei],
Fu, H.Y.[Hui-Yuan],
Ming, A.[Anlong],
Wang, C.M.[Chuan-Ming],
Ma, H.D.[Hua-Dong],
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Chen, S.[Shu],
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Wang, C.W.[Cheng-Wei],
Chen, B.Y.[Bao-Ying],
Zeng, J.[Jishen],
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Zhang, Y.[Yabin],
Li, Y.[Yaohui],
Li, Y.[Yang],
Xu, J.W.[Jing-Wen],
Liu, J.Z.[Jian-Zhao],
Liao, Y.T.[Yi-Ting],
Li, J.L.[Jun-Lin],
Yu, Z.[Zihao],
Guan, F.[Fengbin],
Lu, Y.T.[Yi-Ting],
Li, X.[Xin],
Motamednia, H.[Hossein],
Hosseini-Benvidi, S.F.[S. Farhad],
Mahmoudi-Aznaveh, A.[Ahmad],
Mansouri, A.[Azadeh],
Gankhuyag, G.[Ganzorig],
Yoon, K.[Kihwan],
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Fan, H.T.[Hao-Tian],
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Zhao, S.[Shiling],
Dong, W.F.[Wei-Feng],
Yin, H.B.[Hai-Bing],
Zhu, L.[Li],
Wang, Z.L.[Zhi-Ling],
Huang, B.C.[Bing-Chen],
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Celona, L.[Luigi],
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Zhang, W.[Wei],
Cao, W.Z.[Wen-Zhi],
Liu, L.[Limei],
Peng, H.[Han],
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Li, Z.[Zhan],
Cheng, Y.H.[Yi-Hang],
Deng, Y.F.[Yi-Fan],
Li, H.[Haohui],
Qu, B.[Bowen],
Li, Y.[Yao],
Luo, S.Q.[Shu-Qing],
Wang, S.Z.[Shun-Zhou],
Gao, W.[Wei],
Lu, Z.[Zihao],
Conde, M.V.[Marcos V.],
Timofte, R.[Radu],
Wang, X.R.[Xin-Rui],
Chen, Z.B.[Zhi-Bo],
Liao, R.[Ruling],
Ye, Y.[Yan],
Wang, Q.[Qiulin],
Li, B.[Bing],
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Geng, M.[Miao],
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Liang, X.Y.[Xiao-Yu],
Sun, S.[Shangkun],
Ma, X.Y.[Xing-Yuan],
Li, J.[Jiaze],
Yang, M.[Mengduo],
Xu, H.R.[Hao-Ran],
Zhou, J.[Jie],
Zhu, S.[Shiding],
Yu, B.[Bohan],
Chen, P.F.[Peng-Fei],
Xu, X.R.[Xin-Rui],
Shen, J.[Jiabin],
Duan, Z.C.[Zhi-Chao],
Asadi, E.[Erfan],
Liu, J.[Jiahe],
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NTIRE 2024 Quality Assessment of AI-Generated Content Challenge,
NTIRE24(6337-6362)
IEEE DOI
2410
Image quality, Computational modeling,
Quality assessment
BibRef
Yu, Z.[Zihao],
Guan, F.[Fengbin],
Lu, Y.T.[Yi-Ting],
Li, X.[Xin],
Chen, Z.B.[Zhi-Bo],
SF-IQA: Quality and Similarity Integration for AI Generated Image
Quality Assessment,
NTIRE24(6692-6701)
IEEE DOI
2410
Image quality, Measurement, Visualization, Text to image,
Predictive models, Feature extraction, Excavation
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Chahine, N.[Nicolas],
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Huang, Y.[Yipo],
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Sun, W.[Wei],
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Jiang, Y.W.[Yan-Wei],
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Lin, W.S.[Wei-Si],
Zhai, G.T.[Guang-Tao],
Wang, X.Q.[Xiao-Qi],
Liu, J.Q.[Jun-Qi],
Guo, Z.X.[Zi-Xi],
Zhang, Y.[Yun],
Chen, Z.[Zewen],
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Li, B.[Bing],
Duan, Z.C.[Zhi-Chao],
Xu, X.R.[Xin-Rui],
Huang, Y.[Yipo],
Yuan, Q.[Quan],
Sheng, X.F.[Xiang-Fei],
Yang, Z.C.[Zhi-Chao],
Li, L.[Leida],
Fan, H.T.[Hao-Tian],
Kong, F.Y.[Fang-Yuan],
Xu, Y.F.[Yi-Fang],
Sun, W.[Wei],
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Jiang, Y.W.[Yan-Wei],
Wu, H.N.[Hao-Ning],
Zhang, Z.C.[Zi-Cheng],
Jia, J.[Jun],
Zhou, Y.J.[Ying-Jie],
Ji, Z.P.[Zhong-Peng],
Min, X.K.[Xiong-Kuo],
Lin, W.S.[Wei-Si],
Zhai, G.T.[Guang-Tao],
Chen, Z.[Zewen],
Wang, W.[Wen],
Wang, J.[Juan],
Li, B.[Bing],
Wang, X.Q.[Xiao-Qi],
Liu, J.Q.[Jun-Qi],
Guo, Z.X.[Zi-Xi],
Zhang, Y.[Yun],
Deep Portrait Quality Assessment. A NTIRE 2024 Challenge Survey,
NTIRE24(6732-6744)
IEEE DOI
2410
Surveys, Reviews, Lighting, Artificial neural networks,
Quality assessment,
smartphone
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Zadtootaghaj, S.[Saman],
Barman, N.[Nabajeet],
Timofte, R.[Radu],
He, C.[Chenlong],
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Zhu, R.X.[Ruo-Xi],
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Wang, H.Q.[Hai-Qiang],
Chen, X.G.[Xiang-Guang],
Meng, W.H.[Wen-Hui],
Pan, X.[Xiang],
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Zhu, H.[Han],
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Chen, Z.Z.[Zhen-Zhong],
Liu, S.[Shan],
Zhang, Z.C.[Zi-Cheng],
Wu, H.N.[Hao-Ning],
Zhou, Y.J.[Ying-Jie],
Li, C.Y.[Chun-Yi],
Liu, X.H.[Xiao-Hong],
Lin, W.S.[Wei-Si],
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Sun, W.[Wei],
Cao, Y.Q.[Yu-Qin],
Jiang, Y.W.[Yan-Wei],
Jia, J.[Jun],
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Min, X.K.[Xiong-Kuo],
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Qi, Z.[Zihao],
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AIS 2024 Challenge on Video Quality Assessment of User-Generated
Content: Methods and Results,
AIS24(5826-5837)
IEEE DOI
2410
Surveys, Learning systems, Video on demand, Reviews,
User-generated content, Quality assessment, IQA
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Wang, Z.[Zhou],
4k or Not? - Automatic Image Resolution Assessment,
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Fang, Z.[Zilin],
Ignatov, A.[Andrey],
Zamfir, E.[Eduard],
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SQAD: Automatic Smartphone Camera Quality Assessment and Benchmarking,
ICCV23(20475-20485)
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WWW Link.
2401
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Lin, Y.B.[Yong-Bing],
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Feature Structure Similarity Index for Hybrid Human and Machine
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ICIP23(1480-1484)
IEEE DOI
2312
BibRef
Chetouani, A.[Aladine],
Comparative Study of Saliency- and Scanpath-Based Approaches for
Patch Selection in Image Quality Assessment,
ICIP23(2670-2674)
IEEE DOI
2312
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Zhao, G.[Ganning],
Magoulianitis, V.[Vasileios],
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Kuo, C.C.J.[C.C. Jay],
LGSQE: Lightweight Generated Sample Quality Evaluation,
ICIP23(1915-1919)
IEEE DOI
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You, J.Y.[Jun-Yong],
Lin, Y.[Yuan],
Korhonen, J.[Jari],
Half of an Image is Enough for Quality Assessment,
ICIP23(61-65)
IEEE DOI
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Chahine, N.[Nicolas],
Calarasanu, A.S.[Ana-Stefania],
Garcia-Civiero, D.[Davide],
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An Image Quality Assessment Dataset for Portraits,
CVPR23(9968-9978)
IEEE DOI
2309
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2307
Testing of camera frequency accuracy.
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Chen, G.Y.[Guang Yi],
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ICPR22(1975-1981)
IEEE DOI
2212
Image quality, Sensitivity, Visual systems, Indexes, Remote sensing
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Li, Q.[Qiang],
Yao, Z.L.[Zhao-Liang],
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ICIP22(21-25)
IEEE DOI
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Face recognition, Supervised learning, Self-supervised learning,
Semi-supervised learning, Reliability, Object recognition
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ICIP22(2147-2151)
IEEE DOI
2211
Industries, Visualization, Computational modeling, Transforms,
Visual systems, Prediction algorithms, Quality assessment,
Visual Multimethod Assessment Fusion
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Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Learning for Image Quality Evaluation, CNN, GAN .