Image noise severity metric
We propose in this paper an image noise severity measurement method that correlates well with human's quality perception on the presence of noise in images. In our approach, a 32x32 pixels mask is used to compute the differences between the original and noise-degraded images in terms of the sta...
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| Format: | Article |
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Proceedings of the SPIE
2012
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| Online Access: | http://ir.unimas.my/id/eprint/3013/ |
| _version_ | 1848835124439810048 |
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| author | Bong, D.B.L Khoo, B.E |
| author_facet | Bong, D.B.L Khoo, B.E |
| author_sort | Bong, D.B.L |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | We propose in this paper an image noise severity measurement method that correlates well with human's quality perception on the presence of noise in images. In our approach, a 32x32 pixels mask is used to compute the differences between the original and noise-degraded images in terms of the statistical means and outlier values. These differences are formulated and then compared to the quality scores from the subjective evaluations. The degraded images were distorted by two common types of random noise for images - Gaussian white noise and impulse noise. Experiment results showed that this approach obtained higher correlation compare to classical Peak Signal to Noise Ratio (PSNR) method. |
| first_indexed | 2025-11-15T06:02:53Z |
| format | Article |
| id | unimas-3013 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| last_indexed | 2025-11-15T06:02:53Z |
| publishDate | 2012 |
| publisher | Proceedings of the SPIE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-30132015-03-24T00:27:27Z http://ir.unimas.my/id/eprint/3013/ Image noise severity metric Bong, D.B.L Khoo, B.E TK Electrical engineering. Electronics Nuclear engineering We propose in this paper an image noise severity measurement method that correlates well with human's quality perception on the presence of noise in images. In our approach, a 32x32 pixels mask is used to compute the differences between the original and noise-degraded images in terms of the statistical means and outlier values. These differences are formulated and then compared to the quality scores from the subjective evaluations. The degraded images were distorted by two common types of random noise for images - Gaussian white noise and impulse noise. Experiment results showed that this approach obtained higher correlation compare to classical Peak Signal to Noise Ratio (PSNR) method. Proceedings of the SPIE 2012 Article NonPeerReviewed Bong, D.B.L and Khoo, B.E (2012) Image noise severity metric. Proceedings of the SPIE, 8334. 83343I-83343I. http://adsabs.harvard.edu/abs/2012SPIE.8334E.124B |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Bong, D.B.L Khoo, B.E Image noise severity metric |
| title | Image noise severity metric |
| title_full | Image noise severity metric |
| title_fullStr | Image noise severity metric |
| title_full_unstemmed | Image noise severity metric |
| title_short | Image noise severity metric |
| title_sort | image noise severity metric |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://ir.unimas.my/id/eprint/3013/ http://ir.unimas.my/id/eprint/3013/ |