IEEE Transactions on Image Processing, ISSN 1057-7149, 04/2012, Volume 21, Issue 4, pp. 1500 - 1512
In this paper, we propose a new image quality assessment (IQA) scheme, with emphasis on gradient similarity. Gradients convey important visual information and...
Image quality | Contrast masking | Visualization | gradient similarity | Image coding | Databases | Image edge detection | Transform coding | structural similarity (SSIM) | White noise | human visual system (HVS) | image quality assessment (IQA) | STRUCTURAL SIMILARITY | INFORMATION | MODEL | INDEX | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Artifacts | Reproducibility of Results | Algorithms | Image Interpretation, Computer-Assisted - methods | Sensitivity and Specificity | Signal Processing, Computer-Assisted | Image Enhancement - methods | Subtraction Technique | Pattern Recognition, Automated - methods | Quality Control | Robust statistics | Usage | Distribution (Probability theory) | Mathematical optimization | Analysis
Image quality | Contrast masking | Visualization | gradient similarity | Image coding | Databases | Image edge detection | Transform coding | structural similarity (SSIM) | White noise | human visual system (HVS) | image quality assessment (IQA) | STRUCTURAL SIMILARITY | INFORMATION | MODEL | INDEX | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Artifacts | Reproducibility of Results | Algorithms | Image Interpretation, Computer-Assisted - methods | Sensitivity and Specificity | Signal Processing, Computer-Assisted | Image Enhancement - methods | Subtraction Technique | Pattern Recognition, Automated - methods | Quality Control | Robust statistics | Usage | Distribution (Probability theory) | Mathematical optimization | Analysis
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 06/2015, Volume 26, Issue 6, pp. 1275 - 1286
This paper investigates how to blindly evaluate the visual quality of an image by learning rules from linguistic descriptions. Extensive psychological evidence...
Image quality | Training | Measurement | Deep learning | Visualization | Databases | Image representation | Numerical models | no reference | natural scene statistics (NSS) | image quality assessment (IQA) | Image quality assessment (IQA) | Natural scene statistics (NSS) | No reference | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | NATURAL SCENE STATISTICS | INFORMATION | FRAMEWORK | NEURAL-NETWORK | COMPUTER SCIENCE, THEORY & METHODS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Learning | Models, Theoretical | Biomimetics - methods | Algorithms | Humans | Image Interpretation, Computer-Assisted - methods | Visual Perception | Image Enhancement - methods | Pattern Recognition, Automated - methods | Databases, Factual
Image quality | Training | Measurement | Deep learning | Visualization | Databases | Image representation | Numerical models | no reference | natural scene statistics (NSS) | image quality assessment (IQA) | Image quality assessment (IQA) | Natural scene statistics (NSS) | No reference | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | NATURAL SCENE STATISTICS | INFORMATION | FRAMEWORK | NEURAL-NETWORK | COMPUTER SCIENCE, THEORY & METHODS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Learning | Models, Theoretical | Biomimetics - methods | Algorithms | Humans | Image Interpretation, Computer-Assisted - methods | Visual Perception | Image Enhancement - methods | Pattern Recognition, Automated - methods | Databases, Factual
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 09/2013, Volume 22, Issue 9, pp. 3379 - 3391
We develop a no-reference binocular image quality assessment model that operates on static stereoscopic images. The model deploys 2D and 3D features extracted...
stereoscopic quality assessment | no-reference QA | 3D image quality | Binocular rivalry | STATISTICS | STEREOSCOPIC VIDEO | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Three-dimensional display systems | Usage | Quantum computing | Image processing | Innovations
stereoscopic quality assessment | no-reference QA | 3D image quality | Binocular rivalry | STATISTICS | STEREOSCOPIC VIDEO | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Three-dimensional display systems | Usage | Quantum computing | Image processing | Innovations
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 02/2013, Volume 22, Issue 2, pp. 657 - 667
Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of...
Visualization | Correlation | perceptual image processing | Brightness | image fusion | Dynamic range | structural similarity | High dynamic range image | Standards | Sensitivity | naturalness | image quality assessment | Quality assessment | tone mapping operator | sructural similarity | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | MAPPING OPERATORS | VISIBILITY | CONTRAST | REPRODUCTION | Usage | Image processing | Mathematical statistics | Mathematical optimization | Innovations
Visualization | Correlation | perceptual image processing | Brightness | image fusion | Dynamic range | structural similarity | High dynamic range image | Standards | Sensitivity | naturalness | image quality assessment | Quality assessment | tone mapping operator | sructural similarity | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | MAPPING OPERATORS | VISIBILITY | CONTRAST | REPRODUCTION | Usage | Image processing | Mathematical statistics | Mathematical optimization | Innovations
Journal Article
Computer Graphics Forum, ISSN 0167-7055, 04/2011, Volume 30, Issue 2, pp. 583 - 592
Content‐aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in...
I.3.0 [Computing Methodologies]: Computer Graphics | Image Representation | General I.4.10 [Computing Methodologies]: Image Processing And Computer Vision | COMPUTER SCIENCE, SOFTWARE ENGINEERING | RECOGNITION | COLOR | Computer science | Graphics software | Equipment and supplies | Image processing | Machine vision | Quality management | Studies | Computer simulation | Eyes & eyesight | Image processing systems | Human | Assembling | Color | Images | Preserves | Quality assessment | Assessments | Pixels
I.3.0 [Computing Methodologies]: Computer Graphics | Image Representation | General I.4.10 [Computing Methodologies]: Image Processing And Computer Vision | COMPUTER SCIENCE, SOFTWARE ENGINEERING | RECOGNITION | COLOR | Computer science | Graphics software | Equipment and supplies | Image processing | Machine vision | Quality management | Studies | Computer simulation | Eyes & eyesight | Image processing systems | Human | Assembling | Color | Images | Preserves | Quality assessment | Assessments | Pixels
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 12/2012, Volume 21, Issue 12, pp. 4695 - 4708
We propose a natural scene statistic-based distortion-generic blind/no-reference (NR) image quality assessment (IQA) model that operates in the spatial domain....
denoising | Visualization | Blind quality assessment | no reference image quality assessment | Nonlinear distortion | Humans | natural scene statistics | Prediction algorithms | Indexes | Distortion measurement | spatial domain | INFORMATION | SPARSE | NORMALIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | PARAMETER | ENGINEERING, ELECTRICAL & ELECTRONIC | Real-time control | Usage | Distribution (Probability theory) | Real-time systems | Image processing | Innovations
denoising | Visualization | Blind quality assessment | no reference image quality assessment | Nonlinear distortion | Humans | natural scene statistics | Prediction algorithms | Indexes | Distortion measurement | spatial domain | INFORMATION | SPARSE | NORMALIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | PARAMETER | ENGINEERING, ELECTRICAL & ELECTRONIC | Real-time control | Usage | Distribution (Probability theory) | Real-time systems | Image processing | Innovations
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 08/2011, Volume 20, Issue 8, pp. 2378 - 2386
Image quality assessment (IQA) aims to use computational models to measure the image quality consistently with subjective evaluations. The well-known...
Measurement | Visualization | Gradient | phase congruency (PC) | Image color analysis | Feature extraction | low-level feature | Gabor filters | Indexes | image quality assessment (IQA) | INFORMATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Models, Theoretical | Reproducibility of Results | Algorithms | Humans | Visual Perception | Image Processing, Computer-Assisted - methods | Databases, Factual | Usage | Image processing | Innovations | Mathematical optimization | Pixels | Simulation methods | Studies | Image quality | Similarity | Polycarbonates | Images | Mathematical models | Assessments | Invariants | Image contrast
Measurement | Visualization | Gradient | phase congruency (PC) | Image color analysis | Feature extraction | low-level feature | Gabor filters | Indexes | image quality assessment (IQA) | INFORMATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Models, Theoretical | Reproducibility of Results | Algorithms | Humans | Visual Perception | Image Processing, Computer-Assisted - methods | Databases, Factual | Usage | Image processing | Innovations | Mathematical optimization | Pixels | Simulation methods | Studies | Image quality | Similarity | Polycarbonates | Images | Mathematical models | Assessments | Invariants | Image contrast
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 11/2015, Volume 24, Issue 11, pp. 4408 - 4421
Research on screen content images (SCIs) becomes important as they are increasingly used in multi-device communication applications. In this paper, we present...
Measurement | Image quality | subjective quality assessment | Visualization | Image coding | Databases | objective quality assessment | Transform coding | Quality assessment | Screen content image | quality assessment | INFORMATION | COMPRESSION | SIMILARITY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Measurement | Image quality | subjective quality assessment | Visualization | Image coding | Databases | objective quality assessment | Transform coding | Quality assessment | Screen content image | quality assessment | INFORMATION | COMPRESSION | SIMILARITY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Signal Processing, ISSN 0165-1684, 07/2016, Volume 124, pp. 210 - 219
Image quality assessment (IQA) aims at developing computational models that can precisely and automatically estimate human perceived image quality. To date,...
Image quality assessment | Biologically inspired feature | Percentile pooling | Full-reference | Structural similarity | NATURAL SCENE STATISTICS | INFORMATION | PERSON REIDENTIFICATION | CLASSIFICATION | ENGINEERING, ELECTRICAL & ELECTRONIC | PRESERVATION | VISUAL-ATTENTION | VISIBILITY | COLOR | SIMILARITY | Biomimetics | Analysis | Human | Image quality | Similarity | Images | Distortion | Perception | Mathematical models | Assessments
Image quality assessment | Biologically inspired feature | Percentile pooling | Full-reference | Structural similarity | NATURAL SCENE STATISTICS | INFORMATION | PERSON REIDENTIFICATION | CLASSIFICATION | ENGINEERING, ELECTRICAL & ELECTRONIC | PRESERVATION | VISUAL-ATTENTION | VISIBILITY | COLOR | SIMILARITY | Biomimetics | Analysis | Human | Image quality | Similarity | Images | Distortion | Perception | Mathematical models | Assessments
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 05/2011, Volume 20, Issue 5, pp. 1185 - 1198
Many state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage structure: local quality/distortion measurement followed by...
Weight measurement | Visualization | Computational modeling | Humans | Transforms | information content measure | Image quality | statistical image modeling | pooling | structural similarity (SSIM) | Distortion measurement | peak signal-to-noise-ratio (PSNR) | Gaussian scale mixture (GSM) | image quality assessment (IQA) | ATTENTION | VISUAL SPEED PERCEPTION | STRUCTURAL SIMILARITY | STATISTICS | SCALE MIXTURES | REPRESENTATION | NATURAL IMAGES | NOISE | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | DISTORTION | Reproducibility of Results | Algorithms | Information Storage and Retrieval - methods | Biomimetics | Sensitivity and Specificity | Image Enhancement - methods | Usage | Hypothesis | Ad hoc networks (Computer networks) | Studies | Weighting | Images | Distortion | Mathematical models | Assessments | Signal to noise ratio
Weight measurement | Visualization | Computational modeling | Humans | Transforms | information content measure | Image quality | statistical image modeling | pooling | structural similarity (SSIM) | Distortion measurement | peak signal-to-noise-ratio (PSNR) | Gaussian scale mixture (GSM) | image quality assessment (IQA) | ATTENTION | VISUAL SPEED PERCEPTION | STRUCTURAL SIMILARITY | STATISTICS | SCALE MIXTURES | REPRESENTATION | NATURAL IMAGES | NOISE | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | DISTORTION | Reproducibility of Results | Algorithms | Information Storage and Retrieval - methods | Biomimetics | Sensitivity and Specificity | Image Enhancement - methods | Usage | Hypothesis | Ad hoc networks (Computer networks) | Studies | Weighting | Images | Distortion | Mathematical models | Assessments | Signal to noise ratio
Journal Article
IEEE Transactions on Multimedia, ISSN 1520-9210, 01/2015, Volume 17, Issue 1, pp. 50 - 63
In this paper we propose a new no-reference (NR) image quality assessment (IQA) metric using the recently revealed free-energy-based brain theory and classical...
Measurement | Degradation | Visualization | human visual system | Computational modeling | structural degradation | Predictive models | Brain modeling | Feature extraction | no-reference (NR) | Free energy | image quality assessment (IQA) | COMPUTER SCIENCE, SOFTWARE ENGINEERING | NATURAL SCENE STATISTICS | STRUCTURAL SIMILARITY | COMPUTER SCIENCE, INFORMATION SYSTEMS | TELECOMMUNICATIONS | BRAIN | PREDICTION | Image quality | Fittings | Algorithms | Images | Distortion | Mathematical models | Assessments
Measurement | Degradation | Visualization | human visual system | Computational modeling | structural degradation | Predictive models | Brain modeling | Feature extraction | no-reference (NR) | Free energy | image quality assessment (IQA) | COMPUTER SCIENCE, SOFTWARE ENGINEERING | NATURAL SCENE STATISTICS | STRUCTURAL SIMILARITY | COMPUTER SCIENCE, INFORMATION SYSTEMS | TELECOMMUNICATIONS | BRAIN | PREDICTION | Image quality | Fittings | Algorithms | Images | Distortion | Mathematical models | Assessments
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 06/2010, Volume 19, Issue 6, pp. 1427 - 1441
We present the results of a recent large-scale subjective study of video quality on a collection of videos distorted by a variety of application-relevant...
LIVE video quality database | human visual system | Video on demand | visual perception | Laboratories | Humans | Quality of service | Full reference | perceptual quality assessment | video quality | Visual databases | Image databases | Layout | Video compression | Quality assessment | Large-scale systems | Video quality | Perceptual quality assessment | Human visual system | Visual perception | VISUAL SPEED PERCEPTION | INFORMATION | MODEL | H.264/AVC | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | IMAGE | Reproducibility of Results | Algorithms | Visual Perception - physiology | Image Interpretation, Computer-Assisted - methods | Sensitivity and Specificity | Video Recording - methods | Observer Variation | Image coding | Usage | Mathematical optimization | Methods | Innovations | Data entry | Studies | Data bases | Human | Databases | Images | Distortion | On-line systems | Visual
LIVE video quality database | human visual system | Video on demand | visual perception | Laboratories | Humans | Quality of service | Full reference | perceptual quality assessment | video quality | Visual databases | Image databases | Layout | Video compression | Quality assessment | Large-scale systems | Video quality | Perceptual quality assessment | Human visual system | Visual perception | VISUAL SPEED PERCEPTION | INFORMATION | MODEL | H.264/AVC | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | IMAGE | Reproducibility of Results | Algorithms | Visual Perception - physiology | Image Interpretation, Computer-Assisted - methods | Sensitivity and Specificity | Video Recording - methods | Observer Variation | Image coding | Usage | Mathematical optimization | Methods | Innovations | Data entry | Studies | Data bases | Human | Databases | Images | Distortion | On-line systems | Visual
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 07/2016, Volume 25, Issue 7, pp. 3329 - 3342
It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision...
Measurement | Histograms | natural video | 3D-DCT | Distortion | Feature extraction | video quality assessment | Quality assessment | Spatiotemporal phenomena | no-reference | Video recording | spatiotemporal statistics | NATURAL SCENE STATISTICS | Video quality assessment | MECHANISMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | PREDICTION | ENGINEERING, ELECTRICAL & ELECTRONIC | VISIBILITY | SHAPE | DCT DOMAIN | IMAGE | Video recordings | Research | Analysis | Electric distortion | Quality | Databases | Image processing | Mathematical models | Statistics | Three dimensional
Measurement | Histograms | natural video | 3D-DCT | Distortion | Feature extraction | video quality assessment | Quality assessment | Spatiotemporal phenomena | no-reference | Video recording | spatiotemporal statistics | NATURAL SCENE STATISTICS | Video quality assessment | MECHANISMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | PREDICTION | ENGINEERING, ELECTRICAL & ELECTRONIC | VISIBILITY | SHAPE | DCT DOMAIN | IMAGE | Video recordings | Research | Analysis | Electric distortion | Quality | Databases | Image processing | Mathematical models | Statistics | Three dimensional
Journal Article
EURASIP Journal on Image and Video Processing, ISSN 1687-5176, 12/2009, Volume 2008, Issue 1, pp. 1 - 13
Several metrics have been proposed in literature to assess the perceptual quality of two-dimensional images. However, no similar effort has been devoted to...
Biometrics | Engineering | Pattern Recognition | Signal, Image and Speech Processing | Image Processing and Computer Vision | PERCEPTION | DISPLAYS | VISUAL FATIGUE | MOTION | TECHNOLOGIES | 3-D SHAPE | IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY | 3DTV | COMPRESSION | ALGORITHMS | DEPTH | ENGINEERING, ELECTRICAL & ELECTRONIC | Engineering Sciences | Image Processing | Computer Science | Signal and Image processing
Biometrics | Engineering | Pattern Recognition | Signal, Image and Speech Processing | Image Processing and Computer Vision | PERCEPTION | DISPLAYS | VISUAL FATIGUE | MOTION | TECHNOLOGIES | 3-D SHAPE | IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY | 3DTV | COMPRESSION | ALGORITHMS | DEPTH | ENGINEERING, ELECTRICAL & ELECTRONIC | Engineering Sciences | Image Processing | Computer Science | Signal and Image processing
Journal Article