Synthesized Texture Quality Assessment via Multi-scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients
S. Alireza Golestaneh, and Lina J. Karam
IEEE Conference on Computer Vision and Pattern Recognition Workshop, 2018

In this work, 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.

@inproceedings{golestaneh2017spatially,
  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={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop},
  year={2018}
}