Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering

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

Authors
Bin Wang
Corresponding Author
Bin Wang
Available Online August 2015.
DOI
https://doi.org/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.
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Proceedings
3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015)
Part of series
Advances in Engineering Research
Publication Date
August 2015
ISBN
978-94-6252-100-1
ISSN
2352-5401
DOI
https://doi.org/10.2991/ic3me-15.2015.212How to use a DOI?
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  -