5.3.10.9 Image Quality Evaluation, Human Visual System Based, HVS

Chapter Contents (Back)
Image Quality. Quality Assessment. Subjective Quality Assessment. Perceptual Quality. Human Visual System.
See also Image Quality Evaluation, Perceptual Quality, Subjective Quality.
See also Image Quality Evaluation, Visual Quality, Quality Assessment, and Imaging Models.

Ginesu, G.[Giaime], Massidda, F.[Francesco], Giusto, D.D.[Daniele D.],
A multi-factors approach for image quality assessment based on a human visual system model,
SP:IC(20), No. 4, April 2006, pp. 316-333.
Elsevier DOI Image quality assessment; Human visual system 0605
BibRef

Perra, C., Massidda, F.[Francesco], Giusto, D.D.[Daniele D.],
Image Blockiness Evaluation Based on Sobel Operator,
ICIP05(I: 389-392).
IEEE DOI 0512
BibRef

Zhai, G.T.[Guang-Tao], Zhang, W.J., Yang, X.K.[Xiao-Kang], Xu, Y.,
Image quality metric with an integrated bottom-up and top-down HVS approach,
VISP(153), No. 4, August 2006, pp. 456-460.
WWW Link. 0705
BibRef

Carnec, M.[Mathieu], Le Callet, P.[Patrick], Barba, D.[Dominique],
Objective quality assessment of color images based on a generic perceptual reduced reference,
SP:IC(23), No. 4, April 2008, pp. 239-256.
Elsevier DOI 0711
BibRef
Earlier:
Visual Features for Image Quality Assessment with Reduced Reference,
ICIP05(I: 421-424).
IEEE DOI 0512
BibRef
Earlier:
An image quality assessment method based on perception of structural information,
ICIP03(III: 185-188).
IEEE DOI 0312
BibRef
Earlier: A2, A3, Only:
A robust quality metric for color image quality assessment,
ICIP03(I: 437-440).
IEEE DOI 0312
Image quality; Image quality assessment; Reduced reference; Human visual system; Visual perception BibRef

Sandic-Stankovic, D., Kukolj, D., Le Callet, P.[Patrick],
DIBR synthesized image quality assessment based on morphological pyramids,
3DTV-CON15(1-4)
IEEE DOI 1508
Band-pass filters BibRef

Liu, D.[Delei], Xu, Y.[Yong], Quan, Y.H.[Yu-Hui], Le Callet, P.[Patrick],
Reduced reference image quality assessment using regularity of phase congruency,
SP:IC(29), No. 8, 2014, pp. 844-855.
Elsevier DOI 1410
Reduced-reference image quality assessment BibRef

Liu, D.[Delei], Li, F.Z.[Fu-Zhong], Song, H.B.[Hou-Bing],
Regularity of spectral residual for reduced reference image quality assessment,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1135-1141.
DOI Link 1712
BibRef

Chen, Y.[Yin], Blum, R.S.[Rick S.],
A new automated quality assessment algorithm for image fusion,
IVC(27), No. 10, 2 September 2009, pp. 1421-1432.
Elsevier DOI 0906
Image fusion; Image quality; Human visual system model; Contrast BibRef

Lin, W.S.[Wei-Si], Kuo, C.C.J.[C.C. Jay],
Perceptual visual quality metrics: A survey,
JVCIR(22), No. 4, May 2011, pp. 297-312.
Elsevier DOI 1104
Human visual system (HVS); Vision-based model; Signal-driven model; Signal decomposition; Just-noticeable distortion; Visual attention; Common feature and artifact detection; Full reference; No reference; Reduced reference BibRef

Liu, J.[Jun], Huang, J.[Junyi], Liu, S.G.[Shu-Guang], Li, H.[Huali], Zhou, Q.M.[Qi-Ming], Liu, J.C.[Jun-Chen],
Human visual system consistent quality assessment for remote sensing image fusion,
PandRS(105), No. 1, 2015, pp. 79-90.
Elsevier DOI 1506
Image fusion BibRef

Pei, S.C.[Soo-Chang], Chen, L.H.[Li-Heng],
Image Quality Assessment Using Human Visual DOG Model Fused With Random Forest,
IP(24), No. 11, November 2015, pp. 3282-3292.
IEEE DOI 1509
feature extraction BibRef

Kim, H., Kim, J., Oh, T., Lee, S.,
Blind Sharpness Prediction for Ultrahigh-Definition Video Based on Human Visual Resolution,
CirSysVideo(27), No. 5, May 2017, pp. 951-964.
IEEE DOI 1705
Geometry, High definition video, Image edge detection, Retina, Spatial resolution, Visualization, Perceptual pooling, perceptual sharpness, video sharpness assessment, viewing, geometry BibRef

Hadizadeh, H.[Hadi], Rajati, A., Bajic, I.V.[Ivan V.],
Saliency-Guided Just Noticeable Distortion Estimation Using the Normalized Laplacian Pyramid,
SPLetters(24), No. 8, August 2017, pp. 1218-1222.
IEEE DOI 1708
distortion, estimation theory, image processing, HVS, JND threshold, human visual system, noise-contaminated version, normalized Laplacian pyramid, pixel-wise JND estimation method, saliency-guided just noticeable distortion estimation, Measurement, Visualization. BibRef

Heydari, M.[Maryam], Cheraaqee, P.[Pooryaa], Mansouri, A.[Azadeh], Mahmoudi-Aznaveh, A.[Ahmad],
A low complexity wavelet-based blind image quality evaluator,
SP:IC(74), 2019, pp. 280-288.
Elsevier DOI 1904
Human visual system, Image quality assessment, Wavelet, NR-IQA, BIQA BibRef

Mansouri, A.[Azadeh], Mahmoudi-Aznaveh, A.[Ahmad],
SSVD: Structural SVD-based image quality assessment,
SP:IC(74), 2019, pp. 54-63.
Elsevier DOI 1904
Human visual system, Image quality assessment, Singular value decomposition(SVD), SSVD BibRef

Chen, W., Gu, K., Lin, W., Yuan, F., Cheng, E.,
Statistical and Structural Information Backed Full-Reference Quality Measure of Compressed Sonar Images,
CirSysVideo(30), No. 2, February 2020, pp. 334-348.
IEEE DOI 2002
Sonar measurements, Entropy, Image quality, Image edge detection, Underwater acoustics, Sonar image, quality evaluation, human visual system BibRef

Zhao, F.[Feng], Huang, S.[Shiwang], Long, R.[Renyan], Zhang, T.T.[Tian-Tian], Na, S.G.[Sang-Gyun],
Perceptual visual quality assessment using deeply-learned gaze shifting kernel,
JVCIR(70), 2020, pp. 102701.
Elsevier DOI 2007
Image quality assessment, Human visual system, SSIM BibRef

Wen, W.Y.[Wen-Ying], Wei, K.K.[Kang-Kang], Fang, Y.M.[Yu-Ming], Zhang, Y.S.[Yu-Shu],
Visual Quality Assessment for Perceptually Encrypted Light Field Images,
CirSysVideo(31), No. 7, July 2021, pp. 2522-2534.
IEEE DOI 2107
Visualization, Encryption, Image databases, Measurement, Visual quality assessment, perceptual encryption, epipolar plane image BibRef

Zhang, L.[Luming], Shang, Y.H.[Yong-Heng], Li, P.[Ping], Luo, H.[Hao], Shao, L.[Ling],
Community-Aware Photo Quality Evaluation by Deeply Encoding Human Perception,
Cyber(52), No. 5, May 2022, pp. 3136-3146.
IEEE DOI 2206
Visualization, Semantics, Image quality, Visual perception, Training, Computational modeling, Adaptation models, Community, deep feature, topic model BibRef


Yin, H.B.[Hai-Bing], Xing, Y.F.[Ya-Fen], Xia, G.J.[Guang-Jing], Huang, X.F.[Xiao-Feng], Yan, C.G.[Cheng-Gang],
Improving Just Noticeable Difference Model by Leveraging Temporal HVS Perception Characteristics,
MMMod20(I:87-98).
Springer DOI 2003
BibRef

Dolhasz, A., Harvey, C., Williams, I.,
Learning to Observe: Approximating Human Perceptual Thresholds for Detection of Suprathreshold Image Transformations,
CVPR20(4796-4806)
IEEE DOI 2008
Observers, Distortion, Task analysis, Sensitivity, Image segmentation, Visualization, Image quality BibRef

Ahn, S., Lee, K., Lee, S.,
Visual entropy: A new framework for quantifying visual information based on human perception,
ICIP17(3485-3489)
IEEE DOI 1803
Discrete cosine transforms, Entropy, Information theory, Sensitivity, visual information BibRef

Mahamud, S.T., Rahmatullah, B.,
Image quality assessment based on properties of HVS and principle of image structure,
ICVNZ15(1-6)
IEEE DOI 1701
image processing BibRef

Dimauro, G., Altomare, N., Scalera, M.,
PQMET: A digital image quality metric based on human visual system,
IPTA14(1-6)
IEEE DOI 1503
discrete cosine transforms BibRef

Wajid, R.[Rameez], Mansoor, A.B.[Atif Bin], Pedersen, M.[Marius],
A Human Perception Based Performance Evaluation of Image Quality Metrics,
ISVC14(I: 303-312).
Springer DOI 1501
BibRef

Fan, S.J.[Shao-Jing], Ng, T.T.[Tian-Tsong], Herberg, J.S.[Jonathan S.], Koenig, B.L.[Bryan L.], Tan, C.Y.C.[Cheston Y.C.], Wang, R.D.[Rang-Ding],
An Automated Estimator of Image Visual Realism Based on Human Cognition,
CVPR14(4201-4208)
IEEE DOI 1409
Visual realism; human cognition; perception Perceptual realism. BibRef

Ponomarenko, N.N.[Nikolay N.], Jin, L.[Lina], Lukin, V.[Vladimir], Egiazarian, K.O.[Karen O.],
Self-Similarity Measure for Assessment of Image Visual Quality,
ACIVS11(459-470).
Springer DOI 1108
BibRef

Ponomarenko, N.N.[Nikolay N.], Lukin, V.[Vladimir], Egiazarian, K.O.[Karen O.],
HVS-metric-based performance analysis of image denoising algorithms,
EUVIP11(156-161).
IEEE DOI 1110
BibRef

Mayache, A., Eude, T., Cherifi, H.,
A comparison of image quality models and metrics based on human visual sensitivity,
ICIP98(III: 409-413).
IEEE DOI 9810
BibRef

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


Last update:Jul 13, 2024 at 15:27:21