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Perceptual Quality Assessment for Screen Content Images by Spatial Continuity

https://doi.org/10.1109/tcsvt.2019.2951747
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781118350089openalex-snapshot
Color in Computer Vision: Fundamentals and Applications
inferredcites →https://doi.org/10.1007/11744047_26openalex-snapshot
Coloring Local Feature Extraction
inferredcites →https://doi.org/10.1007/s11760-017-1166-8openalex-snapshot
On the use of deep learning for blind image quality assessment
inferredcites →https://doi.org/10.1016/0042-6989(85)90020-3openalex-snapshot
Sensitivity for structure gradient in texture discrimination tasks
inferredcites →https://doi.org/10.1016/j.compbiomed.2010.02.008openalex-snapshot
Retinal vessel extraction by matched filter with first-order derivative of Gaussian
inferredcites →https://doi.org/10.1016/j.dsp.2018.12.007openalex-snapshot
Blind quality assessment for screen content images via convolutional neural network
inferredcites →https://doi.org/10.1016/j.ins.2016.02.043openalex-snapshot
Orientation selectivity based visual pattern for reduced-reference image quality assessment
inferredcites →https://doi.org/10.1016/j.neucom.2015.11.101openalex-snapshot
Learning a blind quality evaluation engine of screen content images
inferredcites →https://doi.org/10.1038/scientificamerican0979-150openalex-snapshot
Brain Mechanisms of Vision
inferredcites →https://doi.org/10.1088/0954-898x/5/4/006openalex-snapshot
The statistics of natural images
inferredcites →https://doi.org/10.1109/acssc.2003.1292216openalex-snapshot
Multiscale structural similarity for image quality assessment
inferredcites →https://doi.org/10.1109/cvpr.2013.133openalex-snapshot
Learning without Human Scores for Blind Image Quality Assessment
inferredcites →https://doi.org/10.1109/icip.2006.313132openalex-snapshot
Gradient-Based Structural Similarity for Image Quality Assessment
inferredcites →https://doi.org/10.1109/icip.2015.7350816openalex-snapshot
A highly efficient method for blind image quality assessment
inferredcites →https://doi.org/10.1109/icip.2015.7351037openalex-snapshot
Perceptual screen content image quality assessment and compression
inferredcites →https://doi.org/10.1109/icip.2016.7532323openalex-snapshot
Screen content image quality assessment using edge model
inferredcites →https://doi.org/10.1109/icip.2016.7532725openalex-snapshot
Screen content image quality assessment via convolutional neural network
inferredcites →https://doi.org/10.1109/icpr.1998.711280openalex-snapshot
Differential invariants for color images
inferredcites →https://doi.org/10.1109/iscas.2015.7168586openalex-snapshot
Screen image quality assessment incorporating structural degradation measurement
inferredcites →https://doi.org/10.1109/jetcas.2014.2298919openalex-snapshot
Objective Quality Assessment for Image Retargeting Based on Structural Similarity
inferredcites →https://doi.org/10.1109/jetcas.2016.2598756openalex-snapshot
Subjective and Objective Quality Assessment of Compressed Screen Content Images
inferredcites →https://doi.org/10.1109/lsp.2012.2227726openalex-snapshot
Making a “Completely Blind” Image Quality Analyzer
inferredcites →https://doi.org/10.1109/lsp.2014.2326399openalex-snapshot
Blind Image Quality Assessment Using the Joint Statistics of Generalized Local Binary Pattern
inferredcites →https://doi.org/10.1109/lsp.2014.2372333openalex-snapshot
No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics
inferredcites →https://doi.org/10.1109/lsp.2016.2537321openalex-snapshot
No-Reference Quality Assessment for Multiply-Distorted Images in Gradient Domain
inferredcites →https://doi.org/10.1109/lsp.2016.2599294openalex-snapshot
Gradient Direction for Screen Content Image Quality Assessment
inferredcites →https://doi.org/10.1109/qomex.2014.6982328openalex-snapshot
Subjective quality assessment of Screen Content Images
inferredcites →https://doi.org/10.1109/tcsvt.2017.2710419openalex-snapshot
Blind Image Quality Assessment Using Local Consistency Aware Retriever and Uncertainty Aware Evaluator
inferredcites →https://doi.org/10.1109/tip.2003.819231openalex-snapshot
Hue-preserving color image enhancement without gamut problem
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/tip.2010.2042645openalex-snapshot
Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions
inferredcites →https://doi.org/10.1109/tip.2011.2109730openalex-snapshot
FSIM: A Feature Similarity Index for Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2011.2175935openalex-snapshot
Image Quality Assessment Based on Gradient Similarity
inferredcites →https://doi.org/10.1109/tip.2012.2191563openalex-snapshot
Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain
inferredcites →https://doi.org/10.1109/tip.2012.2214050openalex-snapshot
No-Reference Image Quality Assessment in the Spatial Domain
inferredcites →https://doi.org/10.1109/tip.2013.2293423openalex-snapshot
Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
inferredcites →https://doi.org/10.1109/tip.2014.2346028openalex-snapshot
VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2014.2355716openalex-snapshot
Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features
inferredcites →https://doi.org/10.1109/tip.2015.2426416openalex-snapshot
A Feature-Enriched Completely Blind Image Quality Evaluator
inferredcites →https://doi.org/10.1109/tip.2015.2460467openalex-snapshot
Visual Orientation Selectivity Based Structure Description
inferredcites →https://doi.org/10.1109/tip.2015.2465145openalex-snapshot
Perceptual Quality Assessment of Screen Content Images
inferredcites →https://doi.org/10.1109/tip.2016.2573597openalex-snapshot
Just Noticeable Difference Estimation for Screen Content Images
inferredcites →https://doi.org/10.1109/tip.2016.2577891openalex-snapshot
Sparse Representation Based Image Quality Index with Adaptive Sub-Dictionaries
inferredcites →https://doi.org/10.1109/tip.2016.2579308openalex-snapshot
Toward a No-Reference Image Quality Assessment Using Statistics of Perceptual Color Descriptors
inferredcites →https://doi.org/10.1109/tip.2017.2669840openalex-snapshot
Objective Quality Assessment of Screen Content Images by Uncertainty Weighting
inferredcites →https://doi.org/10.1109/tip.2017.2711279openalex-snapshot
No-Reference Quality Assessment of Screen Content Pictures
inferredcites →https://doi.org/10.1109/tip.2017.2718185openalex-snapshot
ESIM: Edge Similarity for Screen Content Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2017.2735192openalex-snapshot
Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images
inferredcites →https://doi.org/10.1109/tip.2017.2760518openalex-snapshot
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2017.2781307openalex-snapshot
No Reference Quality Assessment for Screen Content Images With Both Local and Global Feature Representation
inferredcites →https://doi.org/10.1109/tip.2018.2839890openalex-snapshot
A Gabor Feature-Based Quality Assessment Model for the Screen Content Images
inferredcites →https://doi.org/10.1109/tip.2018.2851390openalex-snapshot
Quality Assessment of Screen Content Images via Convolutional-Neural-Network-Based Synthetic/Natural Segmentation
inferredcites →https://doi.org/10.1109/tmm.2016.2545398openalex-snapshot
Image Sharpness Assessment by Sparse Representation
inferredcites →https://doi.org/10.1109/tmm.2016.2547343openalex-snapshot
Saliency-Guided Quality Assessment of Screen Content Images
inferredcites →https://doi.org/10.1109/tmm.2016.2601028openalex-snapshot
Blind Image Quality Assessment Using Statistical Structural and Luminance Features
inferredcites →https://doi.org/10.1109/tmm.2017.2700206openalex-snapshot
Blind Image Quality Assessment Based on Rank-Order Regularized Regression
inferredcites →https://doi.org/10.1109/tmm.2019.2894939openalex-snapshot
No-Reference Quality Assessment for Screen Content Images Based on Hybrid Region Features Fusion
inferredcites →https://doi.org/10.1109/tpami.2002.1017623openalex-snapshot
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
inferredcites →https://doi.org/10.1109/tpami.2006.3openalex-snapshot
Boosting color saliency in image feature detection
inferredcites →https://doi.org/10.1109/tsmc.2017.2676180openalex-snapshot
Toward a Blind Quality Predictor for Screen Content Images
inferredcites →https://doi.org/10.1113/jphysiol.1962.sp006837openalex-snapshot
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
inferredcites →https://doi.org/10.1117/12.642569openalex-snapshot
Color preference and perceived color naturalness of digital videos
inferredcites →https://doi.org/10.1145/1961189.1961199openalex-snapshot
LIBSVM
inferredcites →https://doi.org/10.1152/jn.1984.52.6.1106openalex-snapshot
Direction and orientation selectivity of neurons in visual area MT of the macaque
inferredcites →https://doi.org/10.1167/17.1.32openalex-snapshot
Perceptual quality prediction on authentically distorted images using a bag of features approach

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Dual-Anchor Metric Learning for Blind Image Quality Assessment of Screen Content Images
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Distortion-Aware Mutual Constraint for Screen Content Image Quality Assessment
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Informative Evaluation of Images Captured by Camera Traps Based on Production Rules: Invited Paper
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Blind quality assessment of screen content images via edge histogram descriptor and statistical moments
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Blind Multimodal Quality Assessment of Low-Light Images
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Feature Sampling based on Multilayer Perceptive Neural Network for image quality assessment
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No Reference Quality Assessment for Screen Content Images Based on Entire and High-Influence Regions
inferred← citeshttps://doi.org/10.1109/icftic59930.2023.10456158openalex-snapshot
Hybrid CNN-Transformer and Multi-Region Selective Features for No-Reference Screen Content Image Quality Assessment
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Quality Assessment of Screen Content Images Based on Convolutional Neural Network with Dual Pathways
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An Efficient Quality Assessment Method for Screen Content Image Based on Gabor
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No Reference Screen Content Image Quality Assessment Using Proxy Labels
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No-Reference Screen Content Image Quality Assessment via Edge and Visual Salient Feature Fusion Network
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Staged-Learning: Assessing the Quality of Screen Content Images from Distortion Information
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Perceptual Redundancy Estimation of Screen Images via Multi-Domain Sensitivities
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Deep Learning Approach for No-Reference Screen Content Video Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2020.3026817openalex-snapshot
Visual Quality Assessment for Perceptually Encrypted Light Field Images
inferred← citeshttps://doi.org/10.1109/tcsvt.2020.3041639openalex-snapshot
Data-Driven Transform-Based Compressed Image Quality Assessment
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2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30
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Generalizable No-Reference Image Quality Assessment via Deep Meta-Learning
inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3096528openalex-snapshot
Fine-Grained Image Quality Assessment: A Revisit and Further Thinking
inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3103544openalex-snapshot
Assessing Individual VR Sickness Through Deep Feature Fusion of VR Video and Physiological Response
inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3112197openalex-snapshot
Blind Image Quality Index for Authentic Distortions With Local and Global Deep Feature Aggregation
inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3143321openalex-snapshot
Dual-Channel Multi-Task CNN for No-Reference Screen Content Image Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3177518openalex-snapshot
Study of Subjective and Objective Quality Assessment of Night-Time Videos
inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3179744openalex-snapshot
Blind Image Quality Assessment for Authentic Distortions by Intermediary Enhancement and Iterative Training
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Distilling Knowledge From Object Classification to Aesthetics Assessment
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DACNN: Blind Image Quality Assessment via a Distortion-Aware Convolutional Neural Network
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Unsupervised Single-View Synthesis Network via Style Guidance and Prior Distillation
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UNI-IQA: A Unified Approach for Mutual Promotion of Natural and Screen Content Image Quality Assessment
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No Reference Quality Assessment for Screen Content Images Using Stacked Autoencoders in Pictorial and Textual Regions
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Low-Light Images In-the-Wild: A Novel Visibility Perception-Guided Blind Quality Indicator
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Deep Feature Statistics Mapping for Generalized Screen Content Image Quality Assessment
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Visual Quality Assessment of Composite Images: A Compression-Oriented Database and Measurement
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You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality Assessment
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Character Transformation Artifact: Perception, Prediction, and Representative Application in Image Quality Assessment
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Mobile Proxy Caching for Multi-View 3D Videos With Adaptive View Selection
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Online Multicast Traffic Engineering for Multi-View Videos With View Synthesis in SDN
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Subjective Rate Distortion Optimization for Screen Content Coding Based on SVR
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Single image super-resolution via Image Quality Assessment-Guided Deep Learning Network
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Quality Assessment of Screen Content Images Based on Convolutional Neural Network Considering Binocular Visual Mechanism
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Object Detection in Enhanced Drone Imagery using Extended ESRGAN with SSD
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