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Image Quality Assessment Using Contrastive Learning [PDF]
IEEE Transactions on Image Processing, 2022 We consider the problem of obtaining image quality representations in a self-supervised manner. We use prediction of distortion type and degree as an auxiliary task to learn features from an unlabeled image dataset containing a mixture of synthetic and realistic distortions.
Pavan C. Madhusudana +4 more
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An Underwater Image Quality Assessment Metric
IEEE Transactions on Multimedia, 2023 Various image enhancement algorithms are adopted to improve underwater images that often suffer from visual distortions. It is critical to assess the output quality of underwater images undergoing enhancement algorithms, and use the results to optimise underwater imaging systems.
Pengfei Guo +5 more
openaire +2 more sources
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual quality of images in accordance with human subjective perception. Unfortunately, existing NR-IQA methods are far from meeting the needs of predicting accurate quality scores on ...
Sidi Yang +6 more
semanticscholar +1 more source
Image Quality Assessment: Unifying Structure and Texture Similarity [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 Objective measures of image quality generally operate by comparing pixels of a “degraded” image to those of the original. Relative to human observers, these measures are overly sensitive to resampling of texture regions (e.g., replacing one patch of ...
Keyan Ding +3 more
semanticscholar +1 more source
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective [PDF]
Computer Vision and Pattern Recognition, 2023 We aim at advancing blind image quality assessment (BIQA), which predicts the human perception of image quality without any reference information. We develop a general and automated multitask learning scheme for BIQA to exploit auxiliary knowledge from ...
Weixia Zhang +4 more
semanticscholar +1 more source
AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment [PDF]
IEEE transactions on circuits and systems for video technology (Print), 2023 With the rapid advancements of the text-to-image generative model, AI-generated images (AGIs) have been widely applied to entertainment, education, social media, etc.
Chunyi Li +7 more
semanticscholar +1 more source
Goal oriented image quality assessment
IET Image Processing, 2022 The area of image quality assessment(IQA) is an active research area in image processing and computer vision. All IQA algorithms reported in literature are attempting to quantify only the visual quality of the images/videos. An interesting question to be
Kiruthika S., Dr. Masilamani V.
doaj +1 more source
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the perceptual image quality in accordance with subjective evaluations, it is a complex and unsolved problem due to the absence of the pristine reference image.
S. Golestaneh +2 more
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Image quality assessment [PDF]
, 2019 Publisher Summary This chapter examines objective criteria for the evaluation of image quality as perceived by an average human observer. The focus is on image fidelity, i.e., how close an image is to a given original or reference image. This paradigm of image quality assessment (QA) is also known as full reference image QA. Three classes of image QA
Sarah A. Barman +3 more
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TOPIQ: A Top-Down Approach From Semantics to Distortions for Image Quality Assessment [PDF]
IEEE Transactions on Image Processing, 2023 Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed remarkable progress with deep neural networks. Inspired by the characteristics of the human visual system, existing methods typically use a combination of global ...
Chaofeng Chen +7 more
semanticscholar +1 more source