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.C.[Hao-Chen],
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],
Le Blanc, 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, 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
Liu, L.[Lei],
Niu, Z.D.[Zhao-Dong],
Li, Y.[Yabo],
Sun, Q.[Quan],
Multi-Level Convolutional Network for Ground-Based Star Image
Enhancement,
RS(15), No. 13, 2023, pp. 3292.
DOI Link
2307
BibRef
Fang, Y.,
Yan, J.,
Du, R.,
Zuo, Y.,
Wen, W.,
Zeng, Y.,
Li, L.,
Blind Quality Assessment for Tone-Mapped Images by Analysis of
Gradient and Chromatic Statistics,
MultMed(23), 2021, pp. 955-966.
IEEE DOI
2103
Visualization, Degradation, Distortion, Feature extraction,
Quality assessment, Histograms, Dynamic range, High dynamic range,
local binary pattern
BibRef
Zhang, P.D.[Peng-Dan],
Ning, J.F.[Ji-Feng],
Hyperspectral Image Denoising via Group Sparsity Regularized Hybrid
Spatio-Spectral Total Variation,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Hao, X.K.[Xian-Kun],
Li, X.[Xu],
Wu, J.Y.[Jing-Ying],
Wei, B.G.[Bao-Guo],
Song, Y.[Yujuan],
Li, B.[Bo],
A No-Reference Quality Assessment Method for Hyperspectral Sharpened
Images via Benford's Law,
RS(16), No. 7, 2024, pp. 1167.
DOI Link
2404
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],
Zéraï, 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
Face Image Quality .