Abstract
Perceptual quality assessment for synthesized textures is a challenging task. In this paper, we propose a trainingfree reduced-reference (RR) objective quality assessment method that quantifies the perceived quality of synthesized textures. The proposed reduced-reference synthesized texture quality assessment metric is based on measuring the spatial and statistical attributes of the texture image using both image-and gradient-based wavelet coefficients at multiple scales. Performance evaluations on two synthesized texture databases demonstrate that our proposed RR synthesized texture quality metric significantly outperforms both full-reference and RR state-of-the-art quality metrics in predicting the perceived visual quality of the synthesized textures.
Original language | English (US) |
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Title of host publication | Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 |
Publisher | IEEE Computer Society |
Pages | 851-857 |
Number of pages | 7 |
Volume | 2018-June |
ISBN (Electronic) | 9781538661000 |
DOIs | |
State | Published - Dec 13 2018 |
Event | 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 - Salt Lake City, United States Duration: Jun 18 2018 → Jun 22 2018 |
Other
Other | 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 |
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Country/Territory | United States |
City | Salt Lake City |
Period | 6/18/18 → 6/22/18 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering