No-reference Image Quality Assessment Approach by Compressed Sensing and Mixture of Generalized Gaussian Distributions

DOI

10.2991/ic3me-15.2015.212How to use a DOI?

Keywords

Image Quality Assessment; Compressed Sensing; Mixture of Generalized Gaussian Distribution.

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 1095
EP  - 1098
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.212
DO  - 10.2991/ic3me-15.2015.212
ID  - Wang2015/08
ER  -