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Blind Image Quality Assessment: A Brief Survey
December 27, 2023 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Blind Image Quality Assessment: A Brief Survey"
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Authors
Miaohui Wang
arXiv ID
2312.16551
Category
cs.CV: Computer Vision
Cross-listed
cs.MM
Citations
1
Venue
arXiv.org
Last Checked
4 days ago
Abstract
Blind Image Quality Assessment (BIQA) is essential for automatically evaluating the perceptual quality of visual signals without access to the references. In this survey, we provide a comprehensive analysis and discussion of recent developments in the field of BIQA. We have covered various aspects, including hand-crafted BIQAs that focus on distortion-specific and general-purpose methods, as well as deep-learned BIQAs that employ supervised and unsupervised learning techniques. Additionally, we have explored multimodal quality assessment methods that consider interactions between visual and audio modalities, as well as visual and text modalities. Finally, we have offered insights into representative BIQA databases, including both synthetic and authentic distortions. We believe this survey provides valuable understandings into the latest developments and emerging trends for the visual quality community.
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