5.3.10.2 Image Quality Evaluation, Stereoscopic Imagery, Stereo

Chapter Contents (Back)
Image Quality. Stereo. Some related papers here: See also Stereoscopic Viewing, Three Dimensional Visualization, Displays.

Benoit, A.[Alexandre], Le Callet, P.[Patrick], Campisi, P.[Patrizio], Cousseau, R.[Romain],
Quality Assessment of Stereoscopic Images,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0903
BibRef
Earlier:
Using disparity for quality assessment of stereoscopic images,
ICIP08(389-392).
IEEE DOI 0810
BibRef

Yang, J.C.[Jia-Chen], Hou, C.P.[Chun-Ping], Xu, R.[Ran], Lei, J.J.[Jian-Jun],
New metric for stereo image quality assessment based on HVS,
IJIST(20), No. 4, December 2010, pp. 301-307.
DOI Link 1011
BibRef

Shao, F., Lin, W., Gu, S., Jiang, G., Srikanthan, T.,
Perceptual Full-Reference Quality Assessment of Stereoscopic Images by Considering Binocular Visual Characteristics,
IP(22), No. 5, May 2013, pp. 1940-1953.
IEEE DOI 1303
BibRef

Shao, F., Li, K., Lin, W., Jiang, G., Yu, M., Dai, Q.,
Full-Reference Quality Assessment of Stereoscopic Images by Learning Binocular Receptive Field Properties,
IP(24), No. 10, October 2015, pp. 2971-2983.
IEEE DOI 1507
Brain modeling BibRef

Shao, F., Lin, W., Wang, S., Jiang, G., Yu, M., Dai, Q.,
Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images,
Cyber(46), No. 3, March 2016, pp. 730-743.
IEEE DOI 1602
Encoding BibRef

Shao, F., Tian, W., Lin, W., Jiang, G., Dai, Q.,
Toward a Blind Deep Quality Evaluator for Stereoscopic Images Based on Monocular and Binocular Interactions,
IP(25), No. 5, May 2016, pp. 2059-2074.
IEEE DOI 1604
image capture BibRef

Moorthy, A.K.[Anush Krishna], Su, C.C.[Che-Chun], Mittal, A.[Anish], Bovik, A.C.[Alan Conrad],
Subjective evaluation of stereoscopic image quality,
SP:IC(28), No. 8, 2013, pp. 870-883.
Elsevier DOI 1309
Stereoscopic quality BibRef

Chen, M.J.[Ming-Jun], Su, C.C.[Che-Chun], Kwon, D.K.[Do-Kyoung], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Full-reference quality assessment of stereopairs accounting for rivalry,
SP:IC(28), No. 9, 2013, pp. 1143-1155.
Elsevier DOI 1310
Binocular rivalry BibRef

Chen, M.J.[Ming-Jun], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
No-Reference Quality Assessment of Natural Stereopairs,
IP(22), No. 9, 2013, pp. 3379-3391.
IEEE DOI 1308
feature extraction BibRef

Shao, F.[Feng], Li, K.[Kemeng], Lin, W.S.[Wei-Si], Jiang, G.[Gangyi], Yu, M.[Mei],
Using Binocular Feature Combination for Blind Quality Assessment of Stereoscopic Images,
SPLetters(22), No. 10, October 2015, pp. 1548-1551.
IEEE DOI 1506
feature extraction BibRef

Yang, J.C.[Jia-Chen], Liu, Y.[Yun], Gao, Z.Q.[Zhi-Qun], Chu, R.R.[Rong-Rong], Song, Z.J.[Zhan-Jie],
A perceptual stereoscopic image quality assessment model accounting for binocular combination behavior,
JVCIR(31), No. 1, 2015, pp. 138-145.
Elsevier DOI 1508
Binocular vision BibRef

Ryu, S.C.[Seung-Chul], Sohn, K.H.[Kwang-Hoon],
No-Reference Quality Assessment for Stereoscopic Images Based on Binocular Quality Perception,
CirSysVideo(24), No. 4, April 2014, pp. 591-602.
IEEE DOI 1405
computer vision BibRef

Ryu, S.C.[Seung-Chul], Kim, D.H.[Dong Hyun], Sohn, K.H.[Kwang-Hoon],
Stereoscopic image quality metric based on binocular perception model,
ICIP12(609-612).
IEEE DOI 1302
BibRef

Ryu, S.C.[Seung-Chul], Sohn, K.H.[Kwang-Hoon],
No-reference perceptual blur model based on inherent sharpness,
ICIP14(580-584)
IEEE DOI 1502
Computational modeling BibRef

Ryu, S.C.[Seung-Chul], Kim, S.[Seungryong], Sohn, K.H.[Kwang-Hoon],
Synthesis quality prediction model based on distortion intolerance,
ICIP14(585-589)
IEEE DOI 1502
Color BibRef

Ryu, S.C.[Seung-Chul], Ham, B.[Bumsub], Sohn, K.H.[Kwang-Hoon],
Contextual information based visual saliency model,
ICIP13(201-205)
IEEE DOI 1402
Computational modeling BibRef

Zhou, W., Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Shao, F.[Feng], Peng, Z.J.[Zong-Ju],
PMFS: A Perceptual Modulated Feature Similarity Metric for Stereoscopic Image Quality Assessment,
SPLetters(21), No. 8, August 2014, pp. 1003-1006.
IEEE DOI 1406
Filtering BibRef

Zhou, W.[Wujie], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Shao, F.[Feng], Peng, Z.J.[Zong-Ju],
Reduced-reference stereoscopic image quality assessment based on view and disparity zero-watermarks,
SP:IC(29), No. 1, 2014, pp. 167-176.
Elsevier DOI 1402
Three dimensional TV BibRef

Yu, M.[Mei], Zheng, K.[Kaihui], Jiang, G.Y.[Gang-Yi], Shao, F.[Feng], Peng, Z.J.[Zong-Ju],
Binocular Perception Based Reduced-Reference Stereo Video Quality Assessment Method,
JVCIR(38), No. 1, 2016, pp. 246-255.
Elsevier DOI 1605
Stereo video quality assessment BibRef

Jiang, Q.P.[Qiu-Ping], Shao, F.[Feng], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Peng, Z.J.[Zong-Ju],
Supervised dictionary learning for blind image quality assessment using quality-constraint sparse coding,
JVCIR(33), No. 1, 2015, pp. 123-133.
Elsevier DOI 1512
Award, JVCI, HM. BibRef
Earlier:
Supervised dictionary learning for blind image quality assessment,
VCIP15(1-4)
IEEE DOI 1605
Blind image quality assessment (BIQA). Databases BibRef

Shao, F.[Feng], Li, K., Lin, W., Jiang, G.Y.[Gang-Yi], Dai, Q.,
Learning Blind Quality Evaluator for Stereoscopic Images Using Joint Sparse Representation,
MultMed(18), No. 10, October 2016, pp. 2104-2114.
IEEE DOI 1610
Computational modeling BibRef

Lv, Y.[Yaqi], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Xu, H.Y.[Hai-Yong], Shao, F.[Feng], Liu, S.S.[Shan-Shan],
Difference of Gaussian statistical features based blind image quality assessment: A deep learning approach,
ICIP15(2344-2348)
IEEE DOI 1512
Blind image quality assessment BibRef

Luo, T.[Ting], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Shao, F.[Feng], Peng, Z.J.[Zong-Ju],
Disparity based stereo image reversible data hiding,
ICIP14(5492-5496)
IEEE DOI 1502
Art BibRef

Zheng, K.[Kaihui], Yu, M.[Mei], Jin, X.[Xin], Jiang, G.Y.[Gang-Yi], Peng, Z.J.[Zong-Ju], Shao, F.[Fen],
New reduced-reference objective stereo image quality assessment model based on human visual system,
3DTV-CON14(1-4)
IEEE DOI 1409
Gaussian distribution BibRef

Du, B.Z.[Bao-Zhen], Yu, M.[Mei], Jiang, G.Y.[Gang-Yi], Zhang, Y.[Yun], Shao, F.[Feng], Peng, Z.J.[Zong-Ju], Zhu, T.Z.[Tian-Zhi],
Novel visibility threshold model for asymmetrically distorted stereoscopic images,
VCIP16(1-4)
IEEE DOI 1701
Complexity theory BibRef

Zhou, J.M.[Jun-Ming], Jiang, G.Y.[Gang-Yi], Mao, X.Y.[Xiang-Ying], Yu, M.[Mei], Shao, F.[Feng], Peng, Z.J.[Zong-Ju], Zhang, Y.[Yun],
Subjective quality analyses of stereoscopic images in 3DTV system,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Md, S.K.[S. Khan], Appina, B.[Balasubramanyam], Channappayya, S.S.[Sumohana S.],
Full-Reference Stereo Image Quality Assessment Using Natural Stereo Scene Statistics,
SPLetters(22), No. 11, November 2015, pp. 1985-1989.
IEEE DOI 1509
Gaussian distribution BibRef

Appina, B.[Balasubramanyam], Khan, S.[Sameeulla], Channappayya, S.S.[Sumohana S.],
No-reference Stereoscopic Image Quality Assessment Using Natural Scene Statistics,
SP:IC(43), No. 1, 2016, pp. 1-14.
Elsevier DOI 1604
Natural scene statistics BibRef

Zhang, Y.[Yi], Chandler, D.M.,
3D-MAD: A Full Reference Stereoscopic Image Quality Estimator Based on Binocular Lightness and Contrast Perception,
IP(24), No. 11, November 2015, pp. 3810-3825.
IEEE DOI 1509
statistical analysis BibRef

Wang, J.H.[Ji-Heng], Rehman, A., Zeng, K.[Kai], Wang, S.Q.[Shi-Qi], Wang, Z.[Zhou],
Quality Prediction of Asymmetrically Distorted Stereoscopic 3D Images,
IP(24), No. 11, November 2015, pp. 3400-3414.
IEEE DOI 1509
distortion BibRef

Wang, J.H.[Ji-Heng], Wang, S.Q.[Shi-Qi], Ma, K., Wang, Z.[Zhou],
Perceptual Depth Quality in Distorted Stereoscopic Images,
IP(26), No. 3, March 2017, pp. 1202-1215.
IEEE DOI 1703
stereo image processing BibRef

Qi, F., Zhao, D., Gao, W.,
Reduced Reference Stereoscopic Image Quality Assessment Based on Binocular Perceptual Information,
MultMed(17), No. 12, December 2015, pp. 2338-2344.
IEEE DOI 1512
Databases BibRef

Xiang, S., Yu, L., Chen, C.W.,
No-Reference Depth Assessment Based on Edge Misalignment Errors for T+D Images,
IP(25), No. 3, March 2016, pp. 1479-1494.
IEEE DOI 1602
Distortion. Quality assessment of depth images. BibRef

Qi, F.[Feng], Zhao, D.B.[De-Bin], Fan, X.P.[Xiao-Peng], Jiang, T.T.[Ting-Ting],
Stereoscopic Video Quality Assessment Based on Visual Attention and Just-Noticeable Difference Models,
SIViP(10), No. 4, April 2016, pp. 737-744.
WWW Link. 1604
BibRef

Qi, F.[Feng], Jiang, T.T.[Ting-Ting], Fan, X.P.[Xiao-Peng], Ma, S.W.[Si-Wei], Zhao, D.B.[De-Bin],
Stereoscopic video quality assessment based on stereo just-noticeable difference model,
ICIP13(34-38)
IEEE DOI 1402
Adaptation models See also Soft mobile video broadcast based on side information refining. BibRef

Li, X.M.[Xiao-Ming], Wang, Y.[Yue], Zhao, D.B.[De-Bin], Jiang, T.T.[Ting-Ting], Zhang, N.[Nan],
Joint just noticeable difference model based on depth perception for stereoscopic images,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Zhou, W., Yu, L.,
Binocular Responses for No-Reference 3D Image Quality Assessment,
MultMed(18), No. 6, June 2016, pp. 1077-1084.
IEEE DOI 1605
Bit error rate BibRef

Jung, Y.J., Kim, H.G., Ro, Y.M.,
Critical Binocular Asymmetry Measure for the Perceptual Quality Assessment of Synthesized Stereo 3D Images in View Synthesis,
CirSysVideo(26), No. 7, July 2016, pp. 1201-1214.
IEEE DOI 1608
extrapolation BibRef

Zhang, W.[Wei], Qu, C.[Chenfei], Ma, L.[Lin], Guan, J.W.[Jing-Wei], Huang, R.[Rui],
Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network,
PR(59), No. 1, 2016, pp. 176-187.
Elsevier DOI 1609
Stereoscopic image BibRef

Lv, Y.[Yaqi], Yu, M.[Mei], Jiang, G.[Gangyi], Shao, F.[Feng], Peng, Z.J.[Zong-Ju], Chen, F.[Fen],
No-reference Stereoscopic Image Quality Assessment Using Binocular Self-similarity and Deep Neural Network,
SP:IC(47), No. 1, 2016, pp. 346-357.
Elsevier DOI 1610
Stereoscopic image quality assessment BibRef

Tamboli, R.R.[Roopak R.], Appina, B.[Balasubramanyam], Channappayya, S.[Sumohana], Jana, S.[Soumya],
Super-multiview content with high angular resolution: 3D quality assessment on horizontal-parallax lightfield display,
SP:IC(47), No. 1, 2016, pp. 42-55.
Elsevier DOI 1610
Full-reference 3D Quality Assessment BibRef

Geng, X.Q.[Xian-Qiu], Shen, L.Q.[Li-Quan], Li, K.[Kai], An, P.[Ping],
A stereoscopic image quality assessment model based on independent component analysis and binocular fusion property,
SP:IC(52), No. 1, 2017, pp. 54-63.
Elsevier DOI 1701
Stereoscopic quality assessment BibRef

Geng, X.Q.[Xian-Qiu], Shen, L.Q.[Li-Quan], An, P.[Ping], Liu, Z.,
Using independent component analysis and binocular combination for stereoscopic image quality assessment,
VCIP16(1-4)
IEEE DOI 1701
Feature extraction BibRef

Chen, F.[Fen], Jiao, R.[Renzhi], Peng, Z.[Zongju], Jiang, G.[Gangyi], Yu, M.[Mei],
Virtual view quality assessment based on shift compensation and visual masking effect,
JVCIR(43), No. 1, 2017, pp. 41-49.
Elsevier DOI 1702
Depth image based rendering BibRef

Ko, H.[Hyunsuk], Song, R.[Rui], Kuo, C.C.J.[C.C. Jay],
A ParaBoost stereoscopic image quality assessment (PBSIQA) system,
JVCIR(45), No. 1, 2017, pp. 156-169.
Elsevier DOI 1704
Stereoscopic images BibRef

Hachicha, W., Kaaniche, M., Beghdadi, A., Cheikh, F.A.,
No-reference stereo image quality assessment based on joint wavelet decomposition and statistical models,
SP:IC(54), No. 1, 2017, pp. 107-117.
Elsevier DOI 1704
Stereo image BibRef

Delis, S., Mademlis, I., Nikolaidis, N., Pitas, I.,
Automatic Detection of 3D Quality Defects in Stereoscopic Videos Using Binocular Disparity,
CirSysVideo(27), No. 5, May 2017, pp. 977-991.
IEEE DOI 1705
Estimation, Measurement, Quality assessment, Stereo image processing, Three-dimensional displays, Videos, Visualization, 3D quality, binocular disparity, stereoscopic video, visual, discomfort BibRef

Yang, J.X.[Jing-Xiang], Zhao, Y.Q.[Yong-Qiang], Yi, C.[Chen], Chan, J.C.W.[Jonathan Cheung-Wai],
No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Yang, J.X.[Jing-Xiang], Zhao, Y.Q.[Yong-Qiang], Chan, J.C.W.[Jonathan Cheung-Wai],
Learning and Transferring Deep Joint Spectral-Spatial Features for Hyperspectral Classification,
GeoRS(55), No. 8, August 2017, pp. 4729-4742.
IEEE DOI 1708
Data mining, Feature extraction, Hyperspectral imaging, Machine learning, Principal component analysis, Training, Convolutional neural network (CNN), deeplearning, feature extraction, hyperspectral classification, transfer, learning See also Coupled Sparse Denoising and Unmixing With Low-Rank Constraint for Hyperspectral Image. BibRef

Jiang, G.Y.[Gang-Yi], Xu, H.Y.[Hai-Yong], Yu, M.[Mei], Luo, T.[Ting], Zhang, Y.[Yun],
Stereoscopic image quality assessment by learning non-negative matrix factorization-based color visual characteristics and considering binocular interactions,
JVCIR(46), No. 1, 2017, pp. 269-279.
Elsevier DOI 1706
Stereoscopic image quality assessment BibRef

Zhou, W.[Wujie], Yu, L.[Lu], Zhou, Y.[Yang], Qiu, W.W.[Wei-Wei], Wu, M.W.[Ming-Wei], Luo, T.[Ting],
Blind quality estimator for 3D images based on binocular combination and extreme learning machine,
PR(71), No. 1, 2017, pp. 207-217.
Elsevier DOI 1707
3D, image, quality, assessment BibRef

Kawabata, N.[Norifumi], Miyao, M.[Masaru],
Multi-View 3D CG Image Quality Assessment for Contrast Enhancement Based on S-CIELAB Color Space,
IEICE(E100-D), No. 7, July 2017, pp. 1448-1462.
WWW Link. 1708
BibRef

Oh, H., Ahn, S., Kim, J., Lee, S.,
Blind Deep S3D Image Quality Evaluation via Local to Global Feature Aggregation,
IP(26), No. 10, October 2017, pp. 4923-4936.
IEEE DOI 1708
Feature extraction, Image quality, Machine learning, Measurement, Three-dimensional displays, Two dimensional displays, Visualization, Stereoscopic 3D, convolutional neural network, deep learning, local feature aggregation, no-reference, image, quality, assessment BibRef

Kim, J., Lee, S.,
Deep Learning of Human Visual Sensitivity in Image Quality Assessment Framework,
CVPR17(1969-1977)
IEEE DOI 1711
Computational modeling, Convolution, Databases, Distortion, Image quality, Sensitivity, Visualization BibRef

Karimi, M., Nejati, M., Soroushmehr, S.M.R., Samavi, S., Karimi, N., Najarian, K.,
Blind Stereo Quality Assessment Based on Learned Features From Binocular Combined Images,
MultMed(19), No. 11, November 2017, pp. 2475-2489.
IEEE DOI 1710
Dictionaries, Estimation, Feature extraction, Phase distortion, binocular combination, no-reference (NR) image quality assessment (IQA), sparse representation, stereo image quality assessment (SIQA), unsupervised, feature, learning BibRef

Liu, Z.G.[Zhi-Guo], Yang, C.[Chifu], Rho, S.[Seungmin], Liu, S.H.[Shao-Hui], Jiang, F.[Feng],
Structured entropy of primitive: Big Data-Based Stereoscopic Image Quality Assessment,
IET-IPR(11), No. 10, October 2017, pp. 854-860.
DOI Link 1710
BibRef


Zhan, J., Niu, Y., Huang, Y.,
Learning from multi metrics for stereoscopic 3D image quality assessment,
IC3D16(1-8)
IEEE DOI 1703
learning (artificial intelligence) BibRef

Wang, K., Zhou, J., Liu, N., Gu, X.,
Stereoscopic images quality assessment based on deep learning,
VCIP16(1-4)
IEEE DOI 1701
Data preprocessing BibRef

Fan, Y.[Yu], Larabi, M.C.[Mohamed-Chaker], Cheikh, F.A.[Faouzi Alaya], Fernandez-Maloigne, C.[Christine],
On the performance of 3D just noticeable difference models,
ICIP16(1017-1021)
IEEE DOI 1610
Maximum tolerable distortion. Adaptation models BibRef

Hong, W., Yu, L.,
Subjective assessment methodology for super multiview content,
3DTV-CON16(1-4)
IEEE DOI 1610
stereo image processing BibRef

Fezza, S.A., Chetouani, A., Larabi, M.C.,
Universal blind image quality assessment for stereoscopic images,
3DTV-CON16(1-4)
IEEE DOI 1610
image resolution BibRef

Ma, J., An, P.,
Method to quality assessment of stereo images,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Ma, J., An, P., You, Z., Shen, L.,
A novel image quality index for stereo image,
3DTV-CON16(1-4)
IEEE DOI 1610
Gabor filters BibRef

Deng, X.D.[Xiang-Dong], Zheng, G.W.[Guan-Wen], Jia, T.[Tao], Cao, X.,
Limits of brightness and color distortions based on subjective evaluation of stereoscopic images,
IC3D15(1-6)
IEEE DOI 1603
distortion BibRef

Authors not listed on paper. A full-reference stereoscopic image quality metric based on binocular energy and regression analysis,
3DTV-CON15(1-5)
IEEE DOI 1508
Analytical models BibRef

Farid, M.S.[Muhammad Shahid], Lucenteforte, M.[Maurizio], Grangetto, M.[Marco],
Blind depth quality assessment using histogram shape analysis,
3DTV-CON15(1-5)
IEEE DOI 1508
Histograms BibRef

Hachicha, W.[Walid], Beghdadi, A.[Azeddine], Cheikh, F.A.[Faouzi Alaya],
Stereo image quality assessment using a binocular just noticeable difference model,
ICIP13(113-117)
IEEE DOI 1402
Computational modeling BibRef

Boehs, G.[Gustavo], Vieira, M.L.H.[Milton L.H.],
Stereoscopic image quality in virtual environments,
IC3D14(1-8)
IEEE DOI 1503
DH-HEMTs BibRef

Fezza, S.A.[Sid Ahmed], Larabi, M.C.[Mohamed-Chaker], Faraoun, K.M.[Kamel Mohamed],
Stereoscopic image quality metric based on local entropy and binocular just noticeable difference,
ICIP14(2002-2006)
IEEE DOI 1502
Entropy BibRef

Chetouani, A.[Aladine],
An Image Quality Metric with Reference for Multiply Distorted Image,
ACIVS16(477-485).
Springer DOI 1611
BibRef

Chetouani, A.[Aladine],
Full Reference Image Quality Assessment: Limitation,
ICPR14(833-837)
IEEE DOI 1412
BibRef
And:
Full reference image quality metric for stereo images based on Cyclopean image computation and neural fusion,
VCIP14(109-112)
IEEE DOI 1504
BibRef
And:
Neural learning-based image quality metric without reference,
IPTA14(1-6)
IEEE DOI 1503
feature extraction Degradation. feature extraction BibRef

Wang, X.[Xu], Cao, L., Ma, L., Zhou, Y., Kwong, S.[Sam],
Complex singular value decomposition based stereoscopic image quality assessment,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Wang, X.[Xu], Kwong, S.[Sam], Zhang, Y.[Yun], Zhang, Y.[Yun],
Considering binocular spatial sensitivity in stereoscopic image quality assessment,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Chetouani, A.[Aladine], Beghdadi, A.[Azeddine], Deriche, M.[Mohamed],
A universal Full Reference image Quality Metric based on a neural fusion approach,
ICIP10(2517-2520).
IEEE DOI 1009
BibRef
And:
Statistical Modeling of Image Degradation Based on Quality Metrics,
ICPR10(714-717).
IEEE DOI 1008
BibRef

Yang, J.C.[Jia-Chen], Hou, C.P.[Chun-Ping], Zhou, Y.[Yuan], Zhang, Z.Y.[Zhuo-Yun], Guo, J.C.[Ji-Chang],
Objective quality assessment method of stereo images,
3DTV09(1-4).
IEEE DOI 0905
BibRef

Shen, L.[Lili], Yang, J.C.[Jia-Chen], Zhang, Z.Y.[Zhuo-Yun],
Quality Assessment of Stereo Images with Stereo Vision,
CISP09(1-4).
IEEE DOI 0910
BibRef
And:
Stereo Picture Quality Estimation Based on a Multiple Channel HVS Model,
CISP09(1-4).
IEEE DOI 0910
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Quality Evaluation, Perceptual Quality, Subjective Quality, Human Visual System Based, HVS .


Last update:Nov 18, 2017 at 20:56:18