Synthesized Texture Quality Assessment via Multi-Scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients

CVPRW 2018 pp. 738-744

doi:10.1109/CVPRW.2018.00117 /cvprw/2018/golestaneh2018cvprw-synthesized/

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.

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Text

Golestaneh and Karam. "Synthesized Texture Quality Assessment via Multi-Scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00117

Markdown

[Golestaneh and Karam. "Synthesized Texture Quality Assessment via Multi-Scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/golestaneh2018cvprw-synthesized/) doi:10.1109/CVPRW.2018.00117

BibTeX

@inproceedings{golestaneh2018cvprw-synthesized,
  title     = {{Synthesized Texture Quality Assessment via Multi-Scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients}},
  author    = {Golestaneh, S. Alireza and Karam, Lina J.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2018},
  pages     = {738-744},
  doi       = {10.1109/CVPRW.2018.00117},
  url       = {https://mlanthology.org/cvprw/2018/golestaneh2018cvprw-synthesized/}
}