5.3.10.1 No-Reference Image Quality Evaluation

Chapter Contents (Back)
Image Quality. No-Reference Quality.

Chow, T.W.S., Tan, H.Z.,
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Evolutionary algorithms; Wigner distribution; Image fusion; Image enhancement; Quality assessment BibRef

Ludovic, Q.[Quintard], Bringier, B., Larabi, M.C.,
Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric,
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Alparone, L.[Luciano], Aiazzi, B.[Bruno], Baronti, S.[Stefano], Garzelli, A.[Andrea], Nencini, F.[Filippo], Selva, M.[Massimo],
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PhEngRS(74), No. 2, February 2008, pp. 193-200.
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A global index capable of measuring the quality of pansharpened multispectral images and working at the full scale withiut oreforming any preliminary degradation of the data. See also Sensitivity of Pansharpening Methods to Temporal and Instrumental Changes Between Multispectral and Panchromatic Data Sets. BibRef

Gao, X.[Xinbo], Lu, W.[Wen], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long],
Image Quality Assessment Based on Multiscale Geometric Analysis,
IP(18), No. 7, July 2009, pp. 1409-1423.
IEEE DOI 0906
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Earlier: A2, A1, A4, A3:
An image quality assessment metric based contourlet,
ICIP08(1172-1175).
IEEE DOI 0810
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He, L.[Lihuo], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long], Gao, X.[Xinbo],
Sparse representation for blind image quality assessment,
CVPR12(1146-1153).
IEEE DOI 1208
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Ye, P.[Peng], Doermann, D.[David],
No-Reference Image Quality Assessment Using Visual Codebooks,
IP(21), No. 7, July 2012, pp. 3129-3138.
IEEE DOI 1206
BibRef
Earlier:
No-reference image quality assessment based on visual codebook,
ICIP11(3089-3092).
IEEE DOI 1201
BibRef

Xu, J.T.[Jing-Tao], Ye, P.[Peng], Li, Q.H.[Qiao-Hong], Du, H.Q.[Hai-Qing], Liu, Y.[Yong], Doermann, D.[David],
Blind Image Quality Assessment Based on High Order Statistics Aggregation,
IP(25), No. 9, September 2016, pp. 4444-4457.
IEEE DOI 1609
feature extraction BibRef
Earlier: A1, A3, A2, A4, A5, Only:
Local feature aggregation for blind image quality assessment,
VCIP15(1-4)
IEEE DOI 1605
BibRef
Earlier: A1, A3, A2, A4, A5, Only:
Statistical metric fusion for image quality assessment,
VCIP14(133-136)
IEEE DOI 1504
Correlation. image fusion BibRef

Xu, J.T.[Jing-Tao], Ye, P.[Peng], Li, Q.H.[Qiao-Hong], Liu, Y.[Yong], Doermann, D.[David],
No-Reference Document Image Quality Assessment Based on High Order Image Statistics,
ICIP16(3289-3293)
IEEE DOI 1610
Databases See also Visual structural degradation based reduced-reference image quality assessment. BibRef

Ye, P.[Peng], Kumar, J.[Jayant], Doermann, D.[David],
Beyond Human Opinion Scores: Blind Image Quality Assessment Based on Synthetic Scores,
CVPR14(4241-4248)
IEEE DOI 1409
image quality;unsupervised learning BibRef

Ye, P.[Peng], Doermann, D.[David],
Active Sampling for Subjective Image Quality Assessment,
CVPR14(4249-4256)
IEEE DOI 1409
active learning;quality of experience;subjective image quality BibRef

Ye, P.[Peng], Kumar, J.[Jayant], Kang, L.[Le], Doermann, D.[David],
Real-Time No-Reference Image Quality Assessment Based on Filter Learning,
CVPR13(987-994)
IEEE DOI 1309
BibRef
Earlier:
Unsupervised feature learning framework for no-reference image quality assessment,
CVPR12(1098-1105).
IEEE DOI 1208
image quality assessment BibRef

Xu, J.T.[Jing-Tao], Ye, P.[Peng], Liu, Y.[Yong], Doermann, D.[David],
No-reference video quality assessment via feature learning,
ICIP14(491-495)
IEEE DOI 1502
Feature extraction BibRef

Peng, P.[Peng], Li, Z.N.[Ze-Nian],
A Mixture of Experts Approach to Multi-strategy Image Quality Assessment,
ICIAR12(I: 123-130).
Springer DOI 1206
BibRef

Kang, L.[Le], Ye, P.[Peng], Li, Y.[Yi], Doermann, D.[David],
Convolutional Neural Networks for No-Reference Image Quality Assessment,
CVPR14(1733-1740)
IEEE DOI 1409
Convolutional Neural Network;image quality assessment BibRef

Kumar, J.[Jayant], Ye, P.[Peng], Doermann, D.[David],
A Dataset for Quality Assessment of Camera Captured Document Images,
CBDAR13(113-125).
Springer DOI 1404
BibRef

Kang, L.[Le], Ye, P.[Peng], Li, Y.[Yi], Doermann, D.[David],
A deep learning approach to document image quality assessment,
ICIP14(2570-2574)
IEEE DOI 1502
Accuracy BibRef

Ye, P.[Peng], Doermann, D.,
Document Image Quality Assessment: A Brief Survey,
ICDAR13(723-727)
IEEE DOI 1312
document image processing BibRef

Serir, A.[Amina], Beghdadi, A.[Azeddine], Kerouh, F.,
No-reference blur image quality measure based on multiplicative multiresolution decomposition,
JVCIR(24), No. 7, 2013, pp. 911-925.
Elsevier DOI 1309
Blur BibRef

De, K.[Kanjar], Masilamani, V.,
A Spatial Domain Object Separability Based No-Reference Image Quality Measure Using Mean and Variance,
IJIG(13), No. 2, April 2013, pp. 1340005.
DOI Link 1308
BibRef

Li, Y.M.[Yu-Ming], Po, L.M.[Lai-Man], Xu, X.Y.[Xu-Yuan], Feng, L.[Litong],
No-reference image quality assessment using statistical characterization in the shearlet domain,
SP:IC(29), No. 7, 2014, pp. 748-759.
Elsevier DOI 1407
No-reference image quality assessment BibRef

Fang, Y.M.[Yu-Ming], Ma, K.[Kede], Wang, Z.[Zhou], Lin, W.S.[Wei-Si], Fang, Z.J.[Zhi-Jun], Zhai, G.T.[Guang-Tao],
No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics,
SPLetters(22), No. 7, July 2015, pp. 838-842.
IEEE DOI 1412
distortion BibRef

Zhang, L.[Lin], Gu, Z.Y.[Zhong-Yi], Liu, X.[Xiaoxu], Li, H.Y.[Hong-Yu], Lu, J.W.[Jian-Wei],
Training Quality-Aware Filters for No-Reference Image Quality Assessment,
MultMedMag(21), No. 4, October 2014, pp. 67-75.
IEEE DOI 1502
filtering theory BibRef

Zhang, L.[Lin], Zhang, L.[Lei], Mou, X.Q.[Xuan-Qin], Zhang, D.[David],
A comprehensive evaluation of full reference image quality assessment algorithms,
ICIP12(1477-1480).
IEEE DOI 1302
BibRef

Virtanen, T., Nuutinen, M., Vaahteranoksa, M., Oittinen, P., Hakkinen, J.,
CID2013: A Database for Evaluating No-Reference Image Quality Assessment Algorithms,
IP(24), No. 1, January 2015, pp. 390-402.
IEEE DOI 1502
Dataset, Image Quality. cameras BibRef

Nuutinen, M., Virtanen, T., Vaahteranoksa, M., Vuori, T., Oittinen, P., Häkkinen, J.,
CVD2014: A Database for Evaluating No-Reference Video Quality Assessment Algorithms,
IP(25), No. 7, July 2016, pp. 3073-3086.
IEEE DOI 1606
image sequences BibRef

Guan, J.W.[Jing-Wei], Zhang, W.[Wei], Gu, J.[Jason], Ren, H.L.[Hong-Liang],
No-reference blur assessment based on edge modeling,
JVCIR(29), No. 1, 2015, pp. 1-7.
Elsevier DOI 1504
Image quality assessment BibRef

Lee, D.[Dohyoung], Plataniotis, K.N.,
Towards a Full-Reference Quality Assessment for Color Images Using Directional Statistics,
IP(24), No. 11, November 2015, pp. 3950-3965.
IEEE DOI 1509
feature extraction BibRef

Lee, D.[Dohyoung], Plataniotis, K.N.,
Toward a No-Reference Image Quality Assessment Using Statistics of Perceptual Color Descriptors,
IP(25), No. 8, August 2016, pp. 3875-3889.
IEEE DOI 1608
Color BibRef

Zhang, M.[Min], Muramatsu, C., Zhou, X.R., Hara, T., Fujita, H.,
Blind Image Quality Assessment Using the Joint Statistics of Generalized Local Binary Pattern,
SPLetters(22), No. 2, February 2015, pp. 207-210.
IEEE DOI 1410
Gaussian processes BibRef

Zhang, M.[Min], Xie, J.[Jin], Zhou, X.R.[Xiang-Rong], Fujita, H.,
No reference image quality assessment based on local binary pattern statistics,
VCIP13(1-6)
IEEE DOI 1402
feature extraction BibRef

Søgaard, J.[Jacob], Forchhammer, S.[Søren], Korhonen, J.,
No-Reference Video Quality Assessment Using Codec Analysis,
CirSysVideo(25), No. 10, October 2015, pp. 1637-1650.
IEEE DOI 1511
discrete cosine transforms BibRef

Huang, X.[Xin], Søgaard, J.[Jacob], Forchhammer, S.[Søren],
No-reference pixel based video quality assessment for HEVC decoded video,
JVCIR(43), No. 1, 2017, pp. 173-184.
Elsevier DOI 1702
BibRef
Earlier:
No-reference video quality assessment by HEVC codec analysis,
VCIP15(1-4)
IEEE DOI 1605
HEVC analysis. Elastic Net BibRef

Wu, Q., Li, H., Meng, F., Ngan, K.N., Luo, B., Huang, C., Zeng, B.,
Blind Image Quality Assessment Based on Multichannel Feature Fusion and Label Transfer,
CirSysVideo(26), No. 3, March 2016, pp. 425-440.
IEEE DOI 1603
Discrete cosine transforms BibRef

Wu, Q., Li, H., Wang, Z., Meng, F., Luo, B., Li, W., Ngan, K.N.,
Blind Image Quality Assessment Based on Rank-Order Regularized Regression,
MultMed(19), No. 11, November 2017, pp. 2490-2504.
IEEE DOI 1710
Distortion, Image quality, Learning systems, Measurement, Optimization, Predictive models, Training, rank-order, regularized regression BibRef

Gu, K., Wang, S., Zhai, G., Ma, S., Yang, X., Lin, W., Zhang, W., Gao, W.,
Blind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structure,
MultMed(18), No. 3, March 2016, pp. 432-443.
IEEE DOI 1603
Brightness BibRef

Min, X., Ma, K., Gu, K., Zhai, G., Wang, Z., Lin, W.,
Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images,
IP(26), No. 11, November 2017, pp. 5462-5474.
IEEE DOI 1709
Databases, Distortion, Graphics, Image coding, Quality assessment, Transform coding, Video coding, Natural scene image, computer graphic image, high efficiency video coding (HEVC), image quality assessment, screen content compression (SCC), screen, content, image BibRef

Tang, L.J.[Li-Juan], Li, L.[Leida], Gu, K.[Ke], Sun, X.M.[Xing-Ming], Zhang, J.Y.[Jian-Ying],
Blind Quality Index for Camera Images with Natural Scene Statistics and Patch-Based Sharpness Assessment,
JVCIR(40, Part A), No. 1, 2016, pp. 335-344.
Elsevier DOI 1609
Image quality assessment (IQA) See also Sparse Representation-Based Image Quality Index With Adaptive Sub-Dictionaries. BibRef

Li, J.[Jie], Zou, L.[Lian], Yan, J.[Jia], Deng, D.X.[De-Xiang], Qu, T.[Tao], Xie, G.H.[Gui-Hui],
No-reference image quality assessment using Prewitt magnitude based on convolutional neural networks,
SIViP(10), No. 4, April 2016, pp. 609-616.
Springer DOI 1604
BibRef

Hadizadeh, H.[Hadi], Bajic, I.V.[Ivan V.],
No-reference image quality assessment using statistical wavelet-packet features,
PRL(80), No. 1, 2016, pp. 144-149.
Elsevier DOI 1609
Image quality assessment BibRef

Hadizadeh, H.[Hadi], Bajic, I.V.[Ivan V.],
Color Gaussian Jet Features For No-Reference Quality Assessment of Multiply-Distorted Images,
SPLetters(23), No. 12, December 2016, pp. 1717-1721.
IEEE DOI 1612
feature extraction BibRef

Mahmoudpour, S.[Saeed], Kim, M.B.[Man-Bae],
No-reference image quality assessment in complex-shearlet domain,
SIViP(10), No. 8, November 2016, pp. 1465-1472.
WWW Link. 1610
BibRef

Javaran, T.A.[Taiebeh Askari], Hassanpour, H.[Hamid], Abolghasemi, V.[Vahid],
A noise-immune no-reference metric for estimating blurriness value of an image,
SP:IC(47), No. 1, 2016, pp. 218-228.
Elsevier DOI 1610
No-reference metric BibRef

Javaran, T.A.[Taiebeh Askari], Hassanpour, H.[Hamid], Abolghasemi, V.[Vahid],
Non-blind image deconvolution using a regularization based on re-blurring process,
CVIU(154), No. 1, 2017, pp. 16-34.
Elsevier DOI 1612
Non-blind image deconvolution BibRef

Nafchi, H.Z., Shahkolaei, A., Hedjam, R., Cheriet, M.,
MUG: A Parameterless No-Reference JPEG Quality Evaluator Robust to Block Size and Misalignment,
SPLetters(23), No. 11, November 2016, pp. 1577-1581.
IEEE DOI 1609
Discrete cosine transforms BibRef

Li, Q.H.[Qiao-Hong], Lin, W.S.[Wei-Si], Xu, J.T.[Jing-Tao], Fang, Y.M.[Yu-Ming],
Blind Image Quality Assessment Using Statistical Structural and Luminance Features,
MultMed(18), No. 12, December 2016, pp. 2457-2469.
IEEE DOI 1612
Data mining BibRef

Goodall, T.R.[Todd R.], Katsavounidis, I.[Ioannis], Li, Z.[Zhi], Aaron, A.[Anne], Bovik, A.C.[Alan C.],
Blind Picture Upscaling Ratio Prediction,
SPLetters(23), No. 12, December 2016, pp. 1801-1805.
IEEE DOI 1612
image processing BibRef

Yang, L.P.[Lu-Ping], Du, H.Q.[Hai-Qing], Xu, J.T.[Jing-Tao], Liu, Y.[Yong],
Blind image quality assessment on authentically distorted images with perceptual features,
ICIP16(2042-2046)
IEEE DOI 1610
Decision support systems BibRef

Vega, M.T.[Maria Torres], Mocanu, D.C.[Decebal Constantin], Stavrou, S.[Stavros], Liotta, A.[Antonio],
Predictive no-reference assessment of video quality,
SP:IC(52), No. 1, 2017, pp. 20-32.
Elsevier DOI 1701
Quality of experience BibRef

Li, L., Xia, W., Lin, W., Fang, Y., Wang, S.,
No-Reference and Robust Image Sharpness Evaluation Based on Multiscale Spatial and Spectral Features,
MultMed(19), No. 5, May 2017, pp. 1030-1040.
IEEE DOI 1704
Computational modeling BibRef

Ma, C.[Chao], Yang, C.Y.[Chih-Yuan], Yang, X.K.[Xiao-Kang], Yang, M.H.[Ming-Hsuan],
Learning a no-reference quality metric for single-image super-resolution,
CVIU(158), No. 1, 2017, pp. 1-16.
Elsevier DOI 1704
Image quality assessment BibRef

Zhang, Y.[Yi], Phan, T.D.[Thien D.], Chandler, D.M.[Damon M.],
Reduced-reference image quality assessment based on distortion families of local perceived sharpness,
SP:IC(55), No. 1, 2017, pp. 130-145.
Elsevier DOI 1705
Reduced-reference, quality, assessment BibRef

Kundu, D., Ghadiyaram, D., Bovik, A.C., Evans, B.L.,
No-Reference Quality Assessment of Tone-Mapped HDR Pictures,
IP(26), No. 6, June 2017, pp. 2957-2971.
IEEE DOI 1705
Distortion, Feature extraction, Image color analysis, Image quality, Predictive models, Standards, Visualization, Image quality assessment, high dynamic range, natural scene statistics, no-reference BibRef

Kundu, D., Ghadiyaram, D., Bovik, A.C., Evans, B.L.,
Large-Scale Crowdsourced Study for Tone-Mapped HDR Pictures,
IP(26), No. 10, October 2017, pp. 4725-4740.
IEEE DOI 1708
crowdsourcing, visual databases, ESPL-LIVE HDR image database, MEF databases, SDR, bypass HDR creation, high-dynamic range images, human opinion, multiexposure fusion, standard dynamic range images, Algorithm design and analysis, Databases, Dynamic range, Image coding, Observers, Standards, Image quality assessment, high dynamic range, subjective study BibRef

Li, S.[Shuang], Yang, Z.[Zewei], Li, H.S.[Hong-Sheng],
Statistical Evaluation of No-Reference Image Quality Assessment Metrics for Remote Sensing Images,
IJGI(6), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Qin, M.[Min], Lv, X.X.[Xiao-Xin], Chen, X.H.[Xiao-Hui], Wang, W.D.[Wei-Dong],
access icon openaccess Hybrid NSS features for no-reference image quality assessment,
IET-IPR(11), No. 6, June 2017, pp. 443-449.
DOI Link 1706
BibRef

Gu, K., Zhou, J., Qiao, J.F., Zhai, G., Lin, W., Bovik, A.C.,
No-Reference Quality Assessment of Screen Content Pictures,
IP(26), No. 8, August 2017, pp. 4005-4018.
IEEE DOI 1707
image colour analysis, natural scenes, regression analysis, blind picture quality assessment algorithm, blind-NR model, blind-no-reference model, cloud platform, computational efficiency, digital screen content images, global brightness quality, high-fidelity cameras, high-performance full-reference method, image centric application, mobile platform, natural scene images, no-reference quality assessment, objective visual quality prediction, opinion-unaware NR blind screen content IQA algorithm, perceptual quality, picture complexity, regression module, screen content image databases, screen content image quality assessment, screen content pictures, screen content statistics, vehicular platform, video centric application, Adaptation models, Complexity theory, Computational modeling, Distortion, Feature extraction, Image coding, Predictive models, Screen content image, big data, hybrid filter, image complexity description, image quality assessment (IQA), no-reference (NR), opinion-unaware (OU), scene, statistics, model BibRef

Fang, R., Al-Bayaty, R., Wu, D.,
BNB Method for No-Reference Image Quality Assessment,
CirSysVideo(27), No. 7, July 2017, pp. 1381-1391.
IEEE DOI 1707
Feature extraction, Image quality, Measurement, Media, Nonlinear distortion, Support vector machines, Artifact metric, Laplace distribution, image quality assessment (IQA), no-reference, (NR) BibRef

Ma, K., Liu, W., Liu, T., Wang, Z., Tao, D.,
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs,
IP(26), No. 8, August 2017, pp. 3951-3964.
IEEE DOI 1707
differentiation, image processing, learning (artificial intelligence), DIL inferred quality index, DIP inferred quality index, ListNet algorithm, RankNet, blind image quality assessment, digital image quality prediction, dipIQ index, gigantic image space, group maximum differentiation competition method, image processing, learning BIQA model, learning-to-rank discriminable image pairs, listwise L2R algorithm, opinion-unaware BIQA, pairwise learning-to-rank algorithm, quality-discriminable image lists, Electronics packaging, Feature extraction, Image quality, Indexes, Predictive models, Training, Blind image quality assessment (BIQA), RankNet, dipIQ, gMAD, learning-to-rank (L2R), quality-discriminable, image, pair, (DIP) BibRef

Li, J.[Jie], Yan, J.[Jia], Deng, D.X.[De-Xiang], Shi, W.X.[Wen-Xuan], Deng, S.F.[Song-Feng],
No-reference image quality assessment based on hybrid model,
SIViP(11), No. 6, September 2017, pp. 985-992.
Springer DOI 1708
BibRef

Li, Q.H.[Qiao-Hong], Lin, W.S.[Wei-Si], Fang, Y.M.[Yu-Ming],
No-Reference Quality Assessment for Multiply-Distorted Images in Gradient Domain,
SPLetters(23), No. 4, April 2016, pp. 541-545.
IEEE DOI 1604
Databases BibRef

Shao, F.[Feng], Tian, W.J.[Wei-Jun], Lin, W.S.[Wei-Si], Jiang, G.Y.[Gang-Yi], Dai, Q.H.[Qiong-Hai],
Learning Sparse Representation for No-Reference Quality Assessment of Multiply Distorted Stereoscopic Images,
MultMed(19), No. 8, August 2017, pp. 1821-1836.
IEEE DOI 1708
Databases, Distortion, Image quality, Measurement, Stereo image processing, Three-dimensional displays, Visualization, Blind/no reference, binocular combination, multiply distorted stereoscopic image (MDSI), sparse, representation BibRef

Xu, L.[Long], Li, J.[Jia], Lin, W.S.[Wei-Si], Zhang, Y.B.[Yong-Bing], Ma, L.[Lin], Fang, Y.M.[Yu-Ming], Yan, Y.H.[Yi-Hua],
Multi-Task Rank Learning for Image Quality Assessment,
CirSysVideo(27), No. 9, September 2017, pp. 1833-1843.
IEEE DOI 1709
Distortion, Image quality, Predictive models, Solid modeling, Training, Transform coding, Image quality assessment (IQA), machine learning (ML), mean opinion score (MOS), pairwise comparison, rank, learning BibRef

Hu, B.[Bo], Li, L.[Leida], Wu, J.[Jinjian], Wang, S.[Shiqi], Tang, L.[Lu], Qian, J.S.[Jian-Sheng],
No-reference quality assessment of compressive sensing image recovery,
SP:IC(58), No. 1, 2017, pp. 165-174.
Elsevier DOI 1710
Image, quality, assessment BibRef


Huang, R.X.[Ri-Xing],
No reference image quality assessments based on edge-blur measure and its applications in printed sheet blurs classification,
ICIVC17(793-797)
IEEE DOI 1708
Image edge detection, blur classification, edge-blur measure (EBM), no reference image quality assessments, printed, sheet, image BibRef

Outtas, M., Zhang, L., Deforges, O., Hammidouche, W., Serir, A., Cavaro-Menard, C.,
A study on the usability of opinion-unaware no-reference natural image quality metrics in the context of medical images,
ISIVC16(308-313)
IEEE DOI 1704
Biomedical imaging BibRef

Yan, J.[Jia], Zhang, W.X.[Wei-Xia], Feng, T.P.[Tian-Peng],
Blind Image Quality Assessment Based on Natural Redundancy Statistics,
ACCV16(IV: 3-18).
Springer DOI 1704
BibRef

Wu, J., Xia, Z., Ren, Y., Li, H.,
No-reference quality assessment for contrast-distorted image,
IPTA16(1-5)
IEEE DOI 1703
feature extraction BibRef

Wu, Q., Li, H., Meng, F., Ngan, K.N.,
Q-DNN: A quality-aware deep neural network for blind assessment of enhanced images,
VCIP16(1-4)
IEEE DOI 1701
Convolution BibRef

Headlee, J.M., Balster, E.J.[Eric J.], Turri, W.F.[William F.],
A no-reference image enhancement quality metric and fusion technique,
ICVNZ15(1-6)
IEEE DOI 1701
image enhancement BibRef

Li, Y.J., Di, X.G.,
A no-reference infrared image sharpness assessment based on singular value decomposition,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Pan, C., Xu, Y., Yan, Y., Gu, K., Yang, X.,
Exploiting neural models for no-reference image quality assessment,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Qian, X.C.[Xin-Chun], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang],
No-Reference Image Quality Assessment Based on Internal Generative Mechanism,
MMMod17(I: 264-276).
Springer DOI 1701
BibRef

Scott, E.T.[Edward T.], Hemami, S.S.[Sheila. S.],
Image utility estimation using difference-of-Gaussian scale space,
ICIP16(101-105)
IEEE DOI 1610
Databases BibRef

Sankisa, A., Pandremmenou, K., Kondi, L.P., Katsaggelos, A.K.,
A novel cumulative distortion metric and a no-reference sparse prediction model for packet prioritization in encoded video transmission,
ICIP16(2097-2101)
IEEE DOI 1610
Distortion BibRef

Zhang, Y., Cui, W.H., Yang, F., Wu, Z.C.,
No-reference Image Quality Assessment For Zy3 Imagery In Urban Areas Using Statistical Model,
ISPRS16(B3: 949-954).
DOI Link 1610
BibRef

Kim, W., Kim, H., Oh, H., Kim, J., Lee, S.,
No-reference perceptual sharpness assessment for ultra-high-definition images,
ICIP16(86-90)
IEEE DOI 1610
Adaptation models BibRef

Gaata, M., Puech, W., Sadkhn, S., Hasson, S.,
No-reference quality metric for watermarked images based on combining of objective metrics using neural network,
IPTA12(229-234)
IEEE DOI 1503
filtering theory BibRef

Soares, J.R.S.[Joao R.S.], da Silva Cruz, L.A.[Luis A.], Assuncao, P.[Pedro], Marinheiro, R.[Rui],
No-reference lightweight estimation of 3D video objective quality,
ICIP14(763-767)
IEEE DOI 1502
Accuracy BibRef

Zhao, H.J.[Heng-Jun],
No-inference image sharpness assessment based on wavelet transform and image saliency map,
ICWAPR16(43-48)
IEEE DOI 1611
Image edge detection BibRef

Zhao, H.J.[Heng-Jun], Fang, B.[Bin], Tang, Y.Y.[Yuan Yan],
A no-reference image sharpness estimation based on expectation of wavelet transform coefficients,
ICIP13(374-378)
IEEE DOI 1402
Discrete wavelet transforms BibRef

Wu, Q.B.[Qing-Bo], Wang, Z.[Zhou], Li, H.L.[Hong-Liang],
A highly efficient method for blind image quality assessment,
ICIP15(339-343)
IEEE DOI 1512
Image quality assessment BibRef

Jenadeleh, M.[Mohsen], Moghaddam, M.E.[Mohsen Ebrahimi],
Blind Image Quality Assessment Through Wakeby Statistics Model,
ICIAR15(14-21).
Springer DOI 1507
BibRef

Song, L.[Li], Chen, C.[Chen], Xu, Y.[Yi], Xue, G.J.[Gen-Jian], Zhou, Y.[Yi],
Blind image quality assessment based on a new feature of nature scene statistics,
VCIP14(37-40)
IEEE DOI 1504
Gaussian distribution BibRef

Tang, H.X.[Hui-Xuan], Joshi, N.[Neel], Kapoor, A.[Ashish],
Blind Image Quality Assessment Using Semi-supervised Rectifier Networks,
CVPR14(2877-2884)
IEEE DOI 1409
BibRef

Xue, W.F.[Wu-Feng], Zhang, L.[Lei], Mou, X.Q.[Xuan-Qin],
Learning without Human Scores for Blind Image Quality Assessment,
CVPR13(995-1002)
IEEE DOI 1309
bind image quality assessment; clustering; qualiyt aware BibRef

Ramírez-Rozo, T.J.[Thomas J.],
Non-referenced Quality Assessment of Image Processing Methods in Infrared Non-destructive Testing,
CIAP13(II:121-130).
Springer DOI 1309
BibRef

De, K.[Kanjar], Masilamani, V,
A new no-reference image quality measure to determine the quality of a given image using object separability,
IMVIP12(92-95).
IEEE DOI 1302
BibRef

Chu, Y.[Ying], Mou, X.Q.[Xuan-Qin], Hong, W.[Wei], Ji, Z.[Zhen],
A novel no-reference image quality assessment metric based on statistical independence,
VCIP12(1-6).
IEEE DOI 1302
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Ojansivu, V.[Ville], Lepistö, L.[Leena], Ilmoniemi, M.[Martti], Heikkilä, J.[Janne],
Degradation Based Blind Image Quality Evaluation,
SCIA11(306-316).
Springer DOI 1105
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Zhang, Y.[Yan], An, P.[Ping], Zhang, Q.[Qiuwen], Shen, L.Q.[Li-Quan], Zhang, Z.Y.[Zhao-Yang],
A no-reference image quality evaluation based on power spectrum,
3DTV11(1-4).
IEEE DOI 1105
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Serir, A.[Amina],
No-reference blurred image quality assessment,
EUVIP11(168-173).
IEEE DOI 1110
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Luo, H.T.[Hui-Tao],
A training-based no-reference image quality assessment algorithm,
ICIP04(V: 2973-2976).
IEEE DOI 0505
BibRef

Luxen, M.[Marc], Forstner, W.[Wolfgang],
Characterizing Image Quality: Blind Estimation of the Point Spread Function from a Single Image,
PCV02(A: 205).
HTML Version. 0305
BibRef

Li, X.[Xin],
Blind image quality assessment,
ICIP02(I: 449-452).
IEEE DOI 0210
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Quality Evaluation, Stereoscopic Imagery, Stereo .


Last update:Nov 11, 2017 at 13:31:57