Predicting Encoded Picture Quality in Two Steps is a Better Way Article Swipe
YOU?
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· 2018
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.1801.02016
Full-reference (FR) image quality assessment (IQA) models assume a high quality "pristine" image as a reference against which to measure perceptual image quality. In many applications, however, the assumption that the reference image is of high quality may be untrue, leading to incorrect perceptual quality predictions. To address this, we propose a new two-step image quality prediction approach which integrates both no-reference (NR) and full-reference perceptual quality measurements into the quality prediction process. The no-reference module accounts for the possibly imperfect quality of the source (reference) image, while the full-reference component measures the quality differences between the source image and its possibly further distorted version. A simple, yet very efficient, multiplication step fuses the two sources of information into a reliable objective prediction score. We evaluated our two-step approach on a recently designed subjective image database and achieved standout performance compared to full-reference approaches, especially when the reference images were of low quality. The proposed approach is made publicly available at https://github.com/xiangxuyu/2stepQA
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1801.02016
- https://arxiv.org/pdf/1801.02016
- OA Status
- green
- Cited By
- 2
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2782916784
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2782916784Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1801.02016Digital Object Identifier
- Title
-
Predicting Encoded Picture Quality in Two Steps is a Better WayWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-01-06Full publication date if available
- Authors
-
Xiangxu Yu, Christos G. Bampis, Praful Gupta, Alan C. BovikList of authors in order
- Landing page
-
https://arxiv.org/abs/1801.02016Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1801.02016Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1801.02016Direct OA link when available
- Concepts
-
Quality (philosophy), Computer science, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2021: 1, 2018: 1Per-year citation counts (last 5 years)
- References (count)
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20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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