5.3.10.2 Color Image Quality, Hyperspectral Image Quality

Chapter Contents (Back)
Image Quality. Hyperspectral. Color.

Christophe, E., Leger, D., Mailhes, C.,
Quality Criteria Benchmark for Hyperspectral Imagery,
GeoRS(43), No. 9, September 2005, pp. 2103-2114.
IEEE DOI 0509
BibRef

Ludovic, Q.[Quintard], Bringier, B., Larabi, M.C.,
Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric,
ELCVIA(7), No. 3, 2008, pp. xx BibRef 0800

Wang, Y.Q.[Yu-Qing], Zhu, M.[Ming], Pang, H.[Haochen], Wang, Y.[Yong],
Quaternion Based Color Image Quality Assessment Index,
IJIG(11), No. 2, April 2011, pp. 195-206.
DOI Link 1107
BibRef

Wang, Y.Q.[Yu-Qing], Zhu, M.[Ming],
Color Image Quality Assessment Based on Quaternion Representation for the Local Variance Distribution of RGB Channels,
CISP09(1-6).
IEEE DOI 0910
BibRef

Wang, Y.[Yong], Wang, Y.Q.[Yu-Qing], Zhao, X.H.[Xiao-Hui],
Complex number-based image quality assessment using singular value decomposition,
IET-IPR(10), No. 2, 2016, pp. 113-120.
DOI Link 1602
image processing BibRef

Kolaman, A., Yadid-Pecht, O.,
Quaternion Structural Similarity: A New Quality Index for Color Images,
IP(21), No. 4, April 2012, pp. 1526-1536.
IEEE DOI 1204
BibRef

Gong, M.M.[Ming-Ming], Pedersen, M.[Marius],
Spatial pooling for measuring color printing quality attributes,
JVCIR(23), No. 5, July 2012, pp. 685-696.
Elsevier DOI 1205
Pooling; Image quality; Metrics; Color quality; Print quality; Quality attributes; Spatial pooling; Image quality assessment BibRef

Preiss, J., Fernandes, F., Urban, P.,
Color-Image Quality Assessment: From Prediction to Optimization,
IP(23), No. 3, March 2014, pp. 1366-1378.
IEEE DOI 1403
distortion 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

Li, L.[Leida], Zhou, Y.[Yu], Wu, J.J.[Jin-Jian], Qian, J.S.[Jian-Sheng], Chen, B.[Beijing],
Color-Enriched Gradient Similarity for Retouched Image Quality Evaluation,
IEICE(E99-D), No. 3, March 2016, pp. 773-776.
WWW Link. 1604
BibRef

Kottayil, N.K.[Navaneeth K.], Cheng, I.[Irene], Dufaux, F.[Frederic], Basu, A.[Anup],
A color intensity invariant low-level feature optimization framework for image quality assessment,
SIViP(10), No. 6, June 2016, pp. 1169-1176.
Springer DOI 1608
BibRef

Gupta, S.[Savita], Gore, A.[Akshay], Kumar, S.[Satish], Mani, S.[Sneh], Srivastava, P.K.,
Objective color image quality assessment based on Sobel magnitude,
SIViP(11), No. 1, January 2017, pp. 123-128.
Springer DOI 1702
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

Yang, J.X.[Jing-Xiang], Zhao, Y.Q.[Yong-Qiang], Chan, J.C.W.[Jonathan Cheung-Wai],
Hyperspectral and Multispectral Image Fusion via Deep Two-Branches Convolutional Neural Network,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Inamdar, D.[Deep], Leblanc, G.[George], Soffer, R.J.[Raymond J.], Kalacska, M.[Margaret],
The Correlation Coefficient as a Simple Tool for the Localization of Errors in Spectroscopic Imaging Data,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
Hyperspectral data quality. BibRef

Sinno, Z.[Zeina], Caramanis, C.[Constantine], Bovik, A.C.[Alan C.],
Towards a Closed Form Second-Order Natural Scene Statistics Model,
IP(27), No. 7, July 2018, pp. 3194-3209.
IEEE DOI 1805
Natural Scene Statistics. Gaussian distribution, computer vision, correlation methods, image denoising, image representation, image sampling, bivariate correlation models BibRef

Sinno, Z.[Zeina], Bovik, A.C.[Alan C.],
Spatio-Temporal Measures Of Naturalness,
ICIP19(1750-1754)
IEEE DOI 1910
BibRef
Earlier:
On the Natural Statistics of Chromatic Images,
Southwest18(81-84)
IEEE DOI 1809
Natural Scene Statistics, Spatio-Temporal Models, Video Quality. Image color analysis, Correlation, Brain modeling, Visualization, Adaptation models, Image quality, Chromatic Natural Scene Statistics BibRef

Hou, R.[Rui], Hu, Y.[Yang], Zhao, Y.H.[Yun-Hao], Liu, H.[Huan],
Hyperspectral image quality evaluation using generalized regression neural network,
SP:IC(83), 2020, pp. 115785.
Elsevier DOI 2003
Hyperspectral image, Feature extraction, GRNN, The phase-consistent map BibRef

Chen, G.B.[Guo-Bin], Pei, Q.A.[Qi-Ang], Kamruzzaman, M.M.,
Remote sensing image quality evaluation based on deep support value learning networks,
SP:IC(83), 2020, pp. 115783.
Elsevier DOI 2003
Remote sensing image, Feature extraction, Deep support value learning networks, 3D convolutional neural networks BibRef

Chen, G.B.[Guo-Bin], Zhang, Y.[Yu], Wang, S.[Suling],
Hyperspectral remote sensing IQA via learning multiple kernels from mid-level features,
SP:IC(83), 2020, pp. 115804.
Elsevier DOI 2003
Hyperspectral image quality assessment, Mid-level feature, Deep features, Multiple kernel learning, Quality-aware BibRef

Liu, L.[Lei], Sun, M.[Min], Ren, X.[Xiang], Li, X.X.[Xiu-Xian], Zhang, Q.R.[Qiao-Ru], Ma, L.[Li], Li, Y.N.[Yong-Ning], Song, M.[Mo],
Hyperspectral image quality based on convolutional network of multi-scale depth,
JVCIR(71), 2020, pp. 102721.
Elsevier DOI 2009
Hyperspectral image, Multi-scale deep convolutional network, Quality research, Super-resolution processing BibRef


Frackiewicz, M.[Mariusz], Palus, H.[Henryk],
K-Means Color Image Quantization with Deterministic Initialization: New Image Quality Metrics,
ICIAR18(56-61).
Springer DOI 1807
BibRef

Nikonorov, A., Petrov, M., Yakimov, P., Blank, V., Karpeev, S., Skidanov, R., Kazanskiy, N.,
Evaluating imaging quality of the offner hyperspectrometer,
PRRS16(1-6)
IEEE DOI 1704
data acquisition BibRef

Cheng, C.[Cheng], Wang, H.[Hanli],
Quality assessment for color images with tucker decomposition,
ICIP12(1489-1492).
IEEE DOI 1302
BibRef

Dauphin, G., de Lesegno, P.V.,
Analysis and comparison of quality metrics with reference based on uniform colour spaces,
EUVIP10(23-28).
IEEE DOI 1110
BibRef

Hardeberg, J.Y.[Jon Y.],
Recent progress in quantifying colour reproduction quality,
EUVIP11(8-11).
IEEE DOI 1110
BibRef

Pedersen, M.[Marius], Zheng, Y.[Yuanlin], Hardeberg, J.Y.[Jon Yngve],
Evaluation of Image Quality Metrics for Color Prints,
SCIA11(317-326).
Springer DOI 1105
BibRef

Triki, O.[Olfa], Zra, M.[Mourad],
Color Image Compression by Riemannian B-Tree Triangular Coding,
ISVC13(II:572-581).
Springer DOI 1311
BibRef
Earlier: A2, A1:
A Differential-Geometrical Framework for Color Image Quality Measures,
ISVC10(III: 544-553).
Springer DOI 1011
BibRef

Yu, M.[Ming], Liu, H.J.[Hui-Juan], Guo, Y.C.[Ying-Chun], Zhao, D.M.[Dong-Ming],
A Method for Reduced-Reference Color Image Quality Assessment,
CISP09(1-5).
IEEE DOI 0910
BibRef

Okarma, K.[Krzysztof],
A Validation of Combined Metrics for Color Image Quality Assessment,
ICCVG14(1-8).
Springer DOI 1410
BibRef
Earlier:
Hybrid Feature Similarity Approach to Full-Reference Image Quality Assessment,
ICCVG12(212-219).
Springer DOI 1210
BibRef
Earlier:
Two-Dimensional Windowing in the Structural Similarity Index for the Colour Image Quality Assessment,
CAIP09(501-508).
Springer DOI 0909
BibRef

Cui, L.[Li], Allen, A.R.[Alastair R.],
An Image Quality Metric Based on a Colour Appearance Model,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef
Earlier:
An Image Quality Metric based on Corner, Edge and Symmetry Maps,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Lalonde, J.F.[Jean-Francois], Efros, A.A.[Alexei A.],
Using Color Compatibility for Assessing Image Realism,
ICCV07(1-8).
IEEE DOI 0710
Determining whether an image is real or non-realistic. To use in recoloring for realistic compositing. BibRef

Medda, A., DeBrunner, V.,
Color Image Quality Index Based on the UIQI,
Southwest06(213-217).
IEEE DOI 0603
BibRef

Schaefer, G., Nolle, L.,
Quality Metric Based Colour Palette Optimisation,
ICIP06(1793-1796).
IEEE DOI 0610
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Screen Content Image Quality Evaluation .


Last update:Oct 19, 2020 at 15:02:28