No-Reference Image Quality Assessment with Global Statistical Features [PDF]
Journal of Imaging, 2021 The perceptual quality of digital images is often deteriorated during storage, compression, and transmission. The most reliable way of assessing image quality is to ask people to provide their opinions on a number of test images.
Domonkos Varga
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A Brief Survey on No-Reference Image Quality Assessment Methods for Magnetic Resonance Images [PDF]
Journal of Imaging, 2022 No-reference image quality assessment (NR-IQA) methods automatically and objectively predict the perceptual quality of images without access to a reference image.
Igor Stępień, Mariusz Oszust
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IE-IQA: Intelligibility Enriched Generalizable No-Reference Image Quality Assessment [PDF]
Frontiers in Neuroscience, 2021 Image quality assessment (IQA) for authentic distortions in the wild is challenging. Though current IQA metrics have achieved decent performance for synthetic distortions, they still cannot be satisfactorily applied to realistic distortions because of ...
Tianshu Song +4 more
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A Human Visual System Inspired No-Reference Image Quality Assessment Method Based on Local Feature Descriptors [PDF]
Sensors, 2022 Objective quality assessment of natural images plays a key role in many fields related to imaging and sensor technology. Thus, this paper intends to introduce an innovative quality-aware feature extraction method for no-reference image quality assessment
Domonkos Varga
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Quadratic Fitting Model in No-Reference Image Quality Assessment [PDF]
Telfor Journal, 2023 The perceptual quality of image is affected by distortions during compression, delivery and storage. Distortions also impact automatic image quality assessment (IQA) that needs to be highly correlated with subjective scores.
A. Gavrovska +4 more
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Automatic no-reference image quality assessment. [PDF]
Springerplus, 2016 No-reference image quality assessment aims to predict the visual quality of distorted images without examining the original image as a reference. Most no-reference image quality metrics which have been already proposed are designed for one or a set of predefined specific distortion types and are unlikely to generalize for evaluating images degraded ...
Li H, Hu W, Xu ZN.
europepmc +3 more sources
No-Reference Image Quality Assessment Based on the Fusion of Statistical and Perceptual Features [PDF]
Journal of Imaging, 2020 The goal of no-reference image quality assessment (NR-IQA) is to predict the quality of an image as perceived by human observers without using any pristine, reference images.
Domonkos Varga
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No-Reference Image Quality Assessment Based on Dual-Domain Feature Fusion [PDF]
Entropy, 2020 Image quality assessment (IQA) aims to devise computational models to evaluate image quality in a perceptually consistent manner. In this paper, a novel no-reference image quality assessment model based on dual-domain feature fusion is proposed, dubbed ...
Yueli Cui
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No-Reference Image Quality Assessment in the Spatial Domain
IEEE Transactions on Image Processing, 2012 We propose a natural scene statistic-based distortion-generic blind/no-reference (NR) image quality assessment (IQA) model that operates in the spatial domain. The new model, dubbed blind/referenceless image spatial quality evaluator (BRISQUE) does not compute distortion-specific features, such as ringing, blur, or blocking, but instead uses scene ...
Anish Mittal +2 more
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No-Reference Image Quality Assessment Method Based on Visual Parameters
Journal of Electronic Science and Technology, 2019 Recent studies on no-reference image quality assessment (NR-IQA) methods usually learn to evaluate the image quality by regressing from human subjective scores of the training samples. This study presented an NR-IQA method based on the basic image visual
Yu-Hong Liu, Kai-Fu Yang, Hong-Mei Yan
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