BIQWS : efficient Wakeby modeling of natural scene statistics for blind image quality assessment

Jenadeleh, Mohsen; Moghaddam, Mohsen Ebrahimi

BIQWS : efficient Wakeby modeling of natural scene statistics for blind image quality assessment

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Date

2017

Authors

Jenadeleh, Mohsen

Moghaddam, Mohsen Ebrahimi

DOI (citable link)

10.1007/s11042-016-3785-4

Collections

Informatik und Informationswissenschaft

Publication type

Journal article

Publication status

Published

Published in

Multimedia Tools and Applications ; 76 (2017), 12. - pp. 13859-13880. - ISSN 1380-7501. - eISSN 1573-7721

Abstract

In this paper, a universal blind image quality assessment (IQA) algorithm is proposed that works in presence of various distortions. The proposed algorithm is a Blind Image Quality metric based on Wakeby Statistics (BIQWS) which extracts local mean subtraction and contrast normalization (MSCN) coefficients in spatial domain from input image. The MSCN coefficients are used for generating a Wakeby distribution statistical model to extract quality-aware features. The statistical studies indicate that the MSCN coefficients histogram is altered in the presence of various distortions with different severities. These changes are regular and can be used to estimate the type of the distortion and its severity. We extended our previous studies to extract efficient Wakeby distribution model parameters which are more sensitive to changes in MSCN coefficients. These parameters are used to form a quality-aware feature vector. This feature vector is then fed to an SVM (support vector machine) regression model with a nonlinear Kernel to predict the quality score of the input image without any information about the distortion type or reference image. Experimental results show that the image quality index obtained by the proposed method has higher correlation with respect to human perceptual opinions and it is superior in some distortions when compared to some full-reference and other state-of-the-art blind image quality assessment methods.

Subject (DDC)

004 Computer Science

Keywords

Blind image quality assessment, Natural scene statistics, Wakeby distribution model, Support vector machine

Cite This

ISO 690

JENADELEH, Mohsen, Mohsen Ebrahimi MOGHADDAM, 2017. BIQWS : efficient Wakeby modeling of natural scene statistics for blind image quality assessment. In: Multimedia Tools and Applications. 76(12), pp. 13859-13880. ISSN 1380-7501. eISSN 1573-7721. Available under: doi: 10.1007/s11042-016-3785-4

BibTex

@article{Jenadeleh2017-06BIQWS-39650,
  year={2017},
  doi={10.1007/s11042-016-3785-4},
  title={BIQWS : efficient Wakeby modeling of natural scene statistics for blind image quality assessment},
  number={12},
  volume={76},
  issn={1380-7501},
  journal={Multimedia Tools and Applications},
  pages={13859--13880},
  author={Jenadeleh, Mohsen and Moghaddam, Mohsen Ebrahimi}
}

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