No-reference image quality assessment using structural activity
Presuming that human visual perception is highly sensitive to the structural information in a scene, we propose the concept of structural activity (SA) together with a model of SA indicator in a new framework for no-reference (NR) image quality assessment (QA) in this study. The proposed framework e...
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| Veröffentlicht in: | Signal processing 2011-11, Vol.91 (11), p.2575-2588 |
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| container_issue | 11 |
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| container_title | Signal processing |
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| creator | Zhang, Jing Le, Thinh M. Ong, S.H. Nguyen, Truong Q. |
| description | Presuming that human visual perception is highly sensitive to the structural information in a scene, we propose the concept of
structural activity (SA) together with a model of SA indicator in a new framework for
no-reference (NR) image
quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative
full-reference (FR) image quality measures.
► Structural activity-based new framework for no-reference image quality assessment. ► A general model named structural activity indicator working with a variety of image distortions. ► Good agreement with human perceived image quality. |
| doi_str_mv | 10.1016/j.sigpro.2011.05.011 |
| format | Article |
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structural activity (SA) together with a model of SA indicator in a new framework for
no-reference (NR) image
quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative
full-reference (FR) image quality measures.
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structural activity (SA) together with a model of SA indicator in a new framework for
no-reference (NR) image
quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative
full-reference (FR) image quality measures.
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structural activity (SA) together with a model of SA indicator in a new framework for
no-reference (NR) image
quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative
full-reference (FR) image quality measures.
► Structural activity-based new framework for no-reference image quality assessment. ► A general model named structural activity indicator working with a variety of image distortions. ► Good agreement with human perceived image quality.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.sigpro.2011.05.011</doi><tpages>14</tpages></addata></record> |
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| ispartof | Signal processing, 2011-11, Vol.91 (11), p.2575-2588 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Applied sciences Assessments Detection, estimation, filtering, equalization, prediction Estimates Exact sciences and technology Human Image quality Image quality assessment Indicators Information, signal and communications theory No-reference image quality assessment Signal and communications theory Signal processing Signal, noise Structural activity Telecommunications and information theory Visual Visual perception |
| title | No-reference image quality assessment using structural activity |
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