5.3.10.2 Full-Reference Image Quality Evaluation

Chapter Contents (Back)
Image Quality. Full-Reference Quality. Full Reference Quality.
See also Screen Content Image Quality Evaluation.

Wee, C.Y.[Chong-Yaw], Paramesran, R.[Raveendran], Mukundan, R., Jiang, X.D.[Xu-Dong],
Image quality assessment by discrete orthogonal moments,
PR(43), No. 12, December 2010, pp. 4055-4068.
Elsevier DOI 1003
Full-reference (FR); Image quality assessment (QA); Discrete orthogonal moments; Tchebichef; Krawtchouk; Local variants assessment; Moment correlation index BibRef

Nehab, D.[Diego], Hoppe, H.[Hugues], Pedersen, M.[Marius], Hardeberg, J.Y.[Jon Yngve],
Full-Reference Image Quality Metrics: Classification and Evaluation,
FTCGV(7), Issue 1, 2011, pp. 1-80.
DOI Link 1410
Survey, Image Quality. Published March 2012. BibRef

Pedersen, M.[Marius],
Evaluation of 60 full-reference image quality metrics on the CID:IQ,
ICIP15(1588-1592)
IEEE DOI 1512
full-reference; image quality; metrics BibRef

Capodiferro, L., Jacovitti, G., di Claudio, E.D.,
Two-Dimensional Approach to Full-Reference Image Quality Assessment Based on Positional Structural Information,
IP(21), No. 2, February 2012, pp. 505-516.
IEEE DOI 1201
BibRef

Charrier, C.[Christophe], Lézoray, O.[Olivier], Lebrun, G.[Gilles],
Machine learning to design full-reference image quality assessment algorithm,
SP:IC(27), No. 3, March 2012, pp. 209-219.
Elsevier DOI 1203
FR-IQA algorithm; Classification; Theory of evidence; SVM classification; SVM regression
See also Color VQ-Based Image Compression by Manifold Learning. BibRef

Wen, Y.[Yang], Li, Y.[Ying], Zhang, X.H.[Xiao-Hua], Shi, W.Z.[Wu-Zhen], Wang, L.[Lin], Chen, J.W.[Jia-Wei],
A weighted full-reference image quality assessment based on visual saliency,
JVCIR(43), No. 1, 2017, pp. 119-126.
Elsevier DOI 1702
Visual saliency computation BibRef

di Claudio, E.D., Jacovitti, G.,
A Detail-Based Method for Linear Full Reference Image Quality Prediction,
IP(27), No. 1, January 2018, pp. 179-193.
IEEE DOI 1712
affine transforms, gradient methods, image processing, DMOS scale setting, additive noise, affine combination, linear quality metric BibRef

Demirtas, A.M.[A. Murat], Reibman, A.R.[Amy R.], Jafarkhani, H.[Hamid],
Full-Reference Quality Estimation for Images With Different Spatial Resolutions,
IP(23), No. 5, May 2014, pp. 2069-2080.
IEEE DOI 1405
BibRef
And:
Full reference video quality estimation for videos with different spatial resolutions,
ICIP14(1997-2001)
IEEE DOI 1502
BibRef
Earlier:
Image quality estimation for different spatial resolutions,
ICIP13(379-382)
IEEE DOI 1402
image resolution. Estimation. Bit rate BibRef

Demirtas, A.M.[A. Murat], Reibman, A.R.[Amy R.], Jafarkhani, H.[Hamid],
Full-Reference Video Quality Estimation for Videos With Different Spatial Resolutions,
CirSysVideo(26), No. 11, November 2016, pp. 1988-2000.
IEEE DOI 1609
Quality assessment BibRef

Reibman, A.R.[Amy R.], Shirley, K.[Kenneth], Tian, C.[Chao],
A probabilistic pairwise-preference predictor for image quality,
ICIP13(413-417)
IEEE DOI 1402
Data models BibRef

Jadhav, M.[Manisha], Dandawate, Y.H.[Yogesh H.], Pisharoty, N.[Narayan],
Edge-based singular value decomposition for full reference colour image quality assessment,
IJCVR(7), No. 5, 2017, pp. 502-521.
DOI Link 1709
BibRef

Khosravi, M.H.[Mohammad Hossein], Hassanpour, H.[Hamid],
Image quality assessment using a novel region smoothness measure,
JVCIR(60), 2019, pp. 217-228.
Elsevier DOI 1903
Image quality assessment, Full reference, Image region smoothness, Maximally stable extremal region, Percentile averaging BibRef

Kong, Y.Q.[Yan-Qiang], Cui, L.[Liu], Hou, R.[Rui],
Full-reference IPTV image quality assessment by deeply learning structural cues,
SP:IC(83), 2020, pp. 115779.
Elsevier DOI 2003
Full-reference IQA, IPTV, Distance metric, Structural information, Deep model BibRef

Ieremeiev, O.[Oleg], Lukin, V.[Vladimir], Okarma, K.[Krzysztof], Egiazarian, K.O.[Karen O.],
Full-Reference Quality Metric Based on Neural Network to Assess the Visual Quality of Remote Sensing Images,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008

See also JPEG-Based Perceptual Image Coding with Block-Based Image Quality Metric. BibRef

Ding, K.Y.[Ke-Yan], Ma, K.D.[Ke-De], Wang, S.Q.[Shi-Qi], Simoncelli, E.P.[Eero P.],
Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems,
IJCV(129), No. 4, April 2021, pp. 1258-1281.
Springer DOI 2104
BibRef

Lan, T.Y.[Tian-Yi], Riaz, S.[Saleem], Zhang, X.D.[Xuan-De], Mirza, A.[Alina], Afzal, F.[Farkhanda], Iqbal, Z.[Zeshan], Khan, M.A.[Muhammad Attique], Alhaisoni, M.[Majed], Alqahtani, A.[Abdullah],
Federated learning based nonlinear two-stage framework for full-reference image quality assessment: An application for biometric,
IVC(128), 2022, pp. 104588.
Elsevier DOI 2212
Image quality assessment, Activation function, Nonlinearity, Two-stage framework, Deep learning BibRef

Bakurov, I.[Illya], Buzzelli, M.[Marco], Schettini, R.[Raimondo], Castelli, M.[Mauro], Vanneschi, L.[Leonardo],
Full-Reference Image Quality Expression via Genetic Programming,
IP(32), 2023, pp. 1458-1473.
IEEE DOI 2303
Image quality, Visualization, Indexes, Digital images, Distortion measurement, Computational modeling, Visual systems, genetic programming BibRef

Ding, K.[Keyan], Zhong, R.[Rijin], Wang, Z.H.[Zhi-Hua], Yu, Y.[Yang], Fang, Y.M.[Yu-Ming],
Adaptive Structure and Texture Similarity Metric for Image Quality Assessment and Optimization,
MultMed(26), 2024, pp. 5398-5409.
IEEE DOI 2404
Image quality, Measurement, Optimization, Training, Databases, Indexes, Dispersion, Full-reference image quality assessment, texture similarity BibRef

Shen, W.H.[Wen-Hao], Zhou, M.L.[Ming-Liang], Luo, J.[Jun], Li, Z.G.[Zheng-Guo], Kwong, S.[Sam],
Graph-Represented Distribution Similarity Index for Full-Reference Image Quality Assessment,
IP(33), 2024, pp. 3075-3089.
IEEE DOI Code:
WWW Link. 2405
Distortion, Image quality, Distortion measurement, Visualization, Indexes, Image edge detection, Task analysis, graph distribution BibRef


Cao, Y.[Yue], Wan, Z.L.[Zhao-Lin], Ren, D.W.[Dong-Wei], Yan, Z.[Zifei], Zuo, W.M.[Wang-Meng],
Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment,
CVPR22(5841-5851)
IEEE DOI 2210
Image quality, Training, Visualization, Computational modeling, Training data, Semisupervised learning, Boosting, Low-level vision BibRef

Xiao, J.F.[Jun-Feng], Zhang, D.[Di],
Full-Reference Image/Video Quality Assessment Algorithms Based on Contrastive Principal Component Analysis,
ICIVC22(648-653)
IEEE DOI 2301
Image quality, Semantics, Neural networks, Feature extraction, Real-time systems, Quality assessment, Communication networks, contrastive principal component analysis BibRef

Ahn, S.[Sewoong], Choi, Y.[Yeji], Yoon, K.[Kwangjin],
Deep Learning-based Distortion Sensitivity Prediction for Full-Reference Image Quality Assessment,
NTIRE21(344-353)
IEEE DOI 2109
Image quality, Visualization, Sensitivity, Databases, Superresolution, Transform coding, Predictive models BibRef

Eerola, T.[Tuomas], Kämäräinen, J.K.[Joni-Kristian], Lensu, L.[Lasse], Kälviäinen, H.[Heikki],
Framework for Applying Full Reference Digital Image Quality Measures to Printed Images,
SCIA09(99-108).
Springer DOI 0906
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
No-Reference Image Quality Evaluation .


Last update:Jun 17, 2024 at 21:38:11