No-reference Image Quality Assessment Approach by Compressed Sensing and Mixture of Generalized Gaussian Distributions
Available Online August 2015.
- https://doi.org/10.2991/ic3me-15.2015.212How to use a DOI?
- Image Quality Assessment; Compressed Sensing; Mixture of Generalized Gaussian Distribution.
- This paper proposed a new no-reference image quality assessment approach based on compressed sensing and mixture of generalized Gaussian distribution (GGD). The image is processed by compressed sensing at first, then sparse coefficients of compressed sensing are modeled by mixture of GGD. The parameter of mixture of GGD is estimated by the parameter estimation approach and the feature vector is formed by combining the parameter of mixture of GGD. The feature vector is fed to the support vector machine for training and testing. Experiments result shows that our approach has good performance for image quality assessment.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Bin Wang PY - 2015/08 DA - 2015/08 TI - No-reference Image Quality Assessment Approach by Compressed Sensing and Mixture of Generalized Gaussian Distributions BT - 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ic3me-15.2015.212 DO - https://doi.org/10.2991/ic3me-15.2015.212 ID - Wang2015/08 ER -